Ryon AI

Автор: Ryon Agent

  • Executive CoPilot: Enterprise AI That Automates Your Operations From the Inside

    Executive CoPilot: Enterprise AI That Automates Your Operations From the Inside

    Executive CoPilot: Enterprise AI That Automates Your Operations From the Inside

    The Problem With How Executives and Operators Work Today

    Every large organisation has the same problem: the people who most need to be making decisions are the ones spending the most time on tasks that should not require human judgment.

    Searching internal systems for information that should be a 10-second lookup. Drafting reports that aggregate data someone else already compiled. Scheduling meetings across 12 time zones. Writing emails that follow the same structure they have followed for three years.

    This is not a people problem. It is a systems problem. And it is costing organisations far more than the salary hours they can measure.

    Ryon’s Executive CoPilot is built to close it.

    What the Executive CoPilot Does

    The Executive CoPilot is an enterprise-grade AI assistant that integrates directly into your existing internal systems — your CRM, your ERP, your document management platform, your communication tools — and operates from within them.

    This is not a chatbot sitting outside your stack that you paste information into. It has direct access to your systems. It reads your data, executes tasks within your workflows, and surfaces the right information at the right moment — without requiring your team to go looking for it.

    Core operational functions include:

    • Instant information retrieval — ask any question about your business data and get an answer in seconds, not hours
    • Document generation — contracts, reports, briefs, proposals — generated from your templates and your live data
    • Email drafting and communication — context-aware drafts based on prior conversation history and your communication preferences
    • Meeting scheduling — end-to-end coordination across calendars, time zones, and availability windows
    • Reporting automation — regular reports assembled from live system data, delivered on schedule

    Results You Can Measure

    • 80% reduction in manual repetitive tasks
    • 90% faster information search across internal systems
    • 90% faster document generation
    • 90% faster email drafting and call scheduling

    These are not efficiency improvements. They are structural changes to how your teams operate — freeing leadership and operators from execution overhead so they can focus on decisions that actually require them.

    Key Features

    Direct Integration With Your Existing Infrastructure

    The Executive CoPilot connects to the systems you already operate — no migration, no data duplication, no new infrastructure to manage. It becomes a capability layer on top of what you have.

    Role-Based Access and Customisation

    Different teams need different capabilities. The CoPilot is configured with role-based access: a CFO sees financial data and reporting; a sales director sees pipeline and CRM; an operations lead sees logistics and fulfilment. Every role gets a version of the tool built for how they actually work.

    Custom Skills That Expand Over Time

    The initial deployment covers your highest-value repetitive tasks. As the system learns your workflows, new skills are added — continuously expanding the scope of what the CoPilot handles automatically. Teams shift from manual execution to oversight.

    Enterprise-Grade Security and Compliance

    The Executive CoPilot is built to enterprise standards: full data traceability, role-gated access, audit logs, and compliance with the security requirements your infrastructure team will demand. It operates inside your environment, not outside it.

    Broad Capability Coverage

    Document generation, communication drafting, scheduling, reporting, internal search, data retrieval — the capability set is built to cover the full range of high-frequency, low-judgment tasks that consume operational bandwidth at every level of the organisation.

    Who This Is Built For

    • C-suite executives who need faster access to business intelligence without analyst dependency
    • Operations teams drowning in repetitive process execution
    • Sales and account management functions with high-volume CRM and communication workloads
    • Finance teams producing recurring reports from multiple data sources
    • Any organisation where skilled people are spending skilled-people time on unskilled-people tasks

    The Department as a Service Model

    Ryon deploys the Executive CoPilot on a retainer basis — what we call Department as a Service. This is not a software licence. It is an ongoing operational partnership: initial integration, custom skill development, continuous optimisation, and expansion of capability coverage as your needs evolve.

    You are not buying a product. You are acquiring a function — one that keeps getting more capable over time.

    See It in Action

    Explore the live demo: https://ryon-executive-copilot.figma.site

    Book a strategy call to see what this looks like inside your organisation: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • AI Call Center Summariser: Automate Every Call, Eliminate Manual Notes

    AI Call Center Summariser: Automate Every Call, Eliminate Manual Notes

    AI Call Center Summariser: Automate Every Call, Eliminate Manual Notes

    The Hidden Cost No One Is Measuring

    Every call your agent takes ends the same way: the call ends, the agent switches windows, and spends the next 5–10 minutes writing notes.

    That is not a minor inconvenience. Across a 50-agent call center operating at volume, it is a structural drag on your entire operation — costing you calls you never made, revenue you never tracked, and data that goes into a CRM in 50 different formats.

    The average call center agent spends 20–30% of their working day on post-call documentation. That is time that could be calls. It is also time that produces inconsistent, rushed, incomplete notes — which means your CRM is filled with data you cannot trust.

    Ryon’s Call Center Summariser was built to close this gap completely.

    What the Call Center Summariser Does

    The Call Center Summariser is a middleware layer that sits between your telephony system and your CRM. It does not replace either. It connects them — and automates everything in between.

    The moment a call ends:

    1. The conversation is automatically transcribed
    2. An AI summary is generated — structured, consistent, accurate
    3. Key data is extracted: customer intent, action items, sentiment, escalation flags
    4. Everything is pushed directly into your CRM — in the right format, in the right fields

    No manual input from the agent. No delay. No missed details.

    Results That Change Operational Math

    Companies deploying the Call Center Summariser report two headline improvements:

    • 20% increase in daily call capacity — agents are freed from post-call admin and can move immediately to the next call
    • 90% reduction in manual summarisation effort — what used to take 8 minutes takes seconds

    At scale, a 20% increase in call capacity across a 50-agent team is the equivalent of hiring 10 additional agents — without the headcount.

    Key Features

    Works With What You Already Have

    The Call Center Summariser integrates with any telephony system and any CRM your business currently uses. There is no infrastructure migration. No ripping and replacing. It connects on top of your existing stack in days, not months.

    Multilingual by Default

    With support for 150+ languages, the system handles multilingual call centers without custom configuration. Whether your agents are working in French, Arabic, or Mandarin, the transcription and summarisation quality remains consistent.

    Agent Performance Analytics

    Beyond individual call summaries, the system generates analytics on agent performance across calls — average handle time, resolution rates, common escalation triggers. Managers get structured visibility they previously had to manually compile.

    Transparent, Flexible Billing

    Ryon charges on an hourly-usage basis — no large upfront licences, no per-seat pricing that penalises growth. You pay for what you use, with full flexibility to scale up or down.

    Full Technical Customisation

    Every call center has its own workflows, terminology, and CRM structure. The Call Center Summariser is fully adaptable — custom extraction fields, custom summary formats, custom CRM mapping — built to fit your operation precisely.

    Who This Is Built For

    The Call Center Summariser delivers the most value to:

    • High-volume B2C call centers where call throughput directly maps to revenue
    • Enterprise sales teams that need structured CRM data from every customer interaction
    • Financial services and insurance where compliance documentation is mandatory
    • Telecoms, utilities, and logistics operators with large distributed agent teams
    • Any organization where agents spend meaningful time writing notes after calls

    Why Ryon Instead of Standalone Transcription Tools

    Generic transcription tools give you a text file. The Call Center Summariser gives you an outcome.

    The difference is the intelligence layer between the transcript and your CRM: structured extraction, contextual summarisation, direct integration with your existing systems, and analytics that aggregate across thousands of conversations.

    You are not buying a transcription tool. You are buying back 20-30% of your agents’ productive time — and converting it into calls, revenue, and clean data.

    See It in Action

    Explore the live demo: https://ryon-call-center-summariser-analytics.figma.site

    Ready to see what this looks like on your call volumes? Book a strategy call with Ryon.ai — artem@ryon.ai | +33 7 77 72 26 23

  • How We Built a Call Center Solution Processing 50,000 Calls a Day

    How We Built a Call Center Solution Processing 50,000 Calls a Day

    Artem Techman | Founder, Ryon.ai

    How We Built a Call Center Solution Processing 50,000 Calls a Day

    Call center agents spend 40 percent of their shift on post call work.

    They type notes into CRMs. They summarize conversations. They extract customer details like order numbers or complaints.

    One client processed 30,000 calls daily. Agents handled 45 calls each per shift before admin ate the rest. We fixed that.

    What We Built

    Ryon.ai Call Center Summariser sits as middleware. It connects telephony systems to CRMs.

    Calls hit our API endpoint. Audio streams in real time via WebSocket. We transcribe with OpenAI Whisper large v3. Accuracy hits 92 percent on clean audio.

    Next, we feed transcripts to GPT 4o for summarization. It outputs a 150 word summary. Plus structured JSON: customer name, intent, sentiment score from 1 to 10, action items.

    Data posts to the CRM via webhook. Agents see it in 45 seconds post call. No manual entry.

    We support 150 languages. French, Mandarin, Arabic. Detection runs first, then language specific transcription.

    The Architecture

    Full replacement kills adoption. We built middleware instead. It plugs on top of existing telephony and CRM.

    Telephony like Twilio or Genesys sends audio to our ingress gateway on AWS ALB. We use Kubernetes clusters across three regions: eu west 1, us east 1, ap southeast 1.

    Ingress fans out to 200 transcription pods. Each pod handles 250 concurrent streams. We queue with Apache Kafka at 100 MBps throughput.

    Post processing: 50 summarization workers on GPU instances. GPT calls batch in groups of 20. Latency stays under 30 seconds for 95 percent of calls.

    Output routes to CRM APIs. Salesforce, HubSpot, Zendesk. We maintain 50 connectors. Authentication via OAuth 2.0 or API keys.

    Scale hits 50,000 calls daily now. Average call 4.2 minutes. Peak at 4,000 calls per hour. We auto scale pods from 50 to 500 in 90 seconds.

    The middleware approach means clients can swap telephony vendors. Our layer stays. Zero downtime migrations.

    The Results

    Before: Agents spent 12 minutes per call on admin. Total shift 480 minutes. Calls per agent: 32.

    After: Admin drops to 1.2 minutes. Calls per agent: 38. That is 20 percent more volume.

    One client went from 30,000 to 36,000 calls daily. Same 950 agents. Manual summarization time fell 90 percent. From 2 hours to 12 minutes per shift.

    Error rate on data extraction: 3 percent now. Was 18 percent with manual entry. Sentiment scores match human labels 87 percent of the time.

    Cost: /bin/sh.12 per call processed. Telephony billed separately. ROI in 14 days for most clients.

    What Surprised Us

    Noise killed transcription first. 22 percent of calls had background chatter. Accuracy dropped to 71 percent.

    We added RNNoise suppression. Pre processes audio in 200 ms. Accuracy back to 91 percent. It costs 15 percent more CPU but the trade is worth it.

    Second surprise: agents wanted more. Week one usage was 82 percent of all calls. They started requesting custom fields like an upsell opportunity score. We shipped that in sprint two. Adoption beat our 50 percent target.

    Three Lessons for Anyone Building Similar

    Lesson one: Integration rules all. Spend 40 percent of dev time on connectors. We wrote 50. Clients can test in 2 hours.

    Lesson two: Real time feels better than it is. Live transcription feels instant. Summaries can batch for cost. Our GPUs run at 70 percent utilization and we saved 35 percent on inference bills by batching.

    Lesson three: Monitor drift hard. Language models shift. We A/B test weekly on 1,000 gold standard calls. If accuracy dips 2 percent we retrain the prompts.

    Where This Is Going

    We process 50,000 calls today. Target is 200,000 by Q4 2026.

    Next up: voice biometrics to detect fraud in 1.2 seconds. Then real time agent assist during the call itself, with prompts delivered via earpiece. Early tests show 15 percent conversion lift.

    Ryon.ai builds intelligence layers for large companies. This solves one pain point. Many more to come.

    Artem Techman is the founder of Ryon.ai, an AI integration agency for large corporates based in Cannes, France.

  • Support GPT: Resolve 75% of Customer Inquiries Automatically — Without Sacrificing Quality

    Support GPT: Resolve 75% of Customer Inquiries Automatically — Without Sacrificing Quality

    Support GPT: Resolve 75% of Customer Inquiries Automatically — Without Sacrificing Quality

    What Customer Support Costs You That You Cannot See on a Spreadsheet

    The visible cost of customer support is headcount. The invisible cost is everything else.

    Response times that frustrate customers at 11pm when your team is offline. Inconsistency between agents — same question, five different answers, depending on who picks up. Agents spending 60% of their time on tier-1 questions that follow identical patterns. Escalations that happen because the front-line agent did not have access to the right information, not because the issue was genuinely complex.

    These are not edge cases. They are the structural reality of human-only support at scale.

    Ryon’s Support GPT is built to solve all of them simultaneously.

    What Support GPT Does

    Support GPT deploys fully traceable AI agents across your customer-facing communication channels — WhatsApp, Instagram, Telegram, your website — that are trained on your company’s actual processes, documentation, and support logic.

    This is not a scripted chatbot following decision trees. It is an AI that understands your business: your products, your policies, your escalation criteria, your tone of voice. It handles conversations the way your best support agent would — with context, with consistency, and with the ability to adapt to each interaction.

    Every conversation is recorded and structured inside your admin dashboard. You have full visibility into what was resolved, how it was resolved, and where human intervention was required.

    Results

    • 75% of inquiries resolved with zero human involvement
    • Up to 80% reduction in customer support operating costs
    • Faster response times across all channels, 24/7 availability

    A 75% autonomous resolution rate does not mean 75% of easy questions handled and 25% escalated randomly. It means 75% of all inquiries — including complex ones — fully resolved without a human agent ever getting involved. The 25% that reach human agents are genuinely the cases that require human judgment.

    For a 30-person support team, an 80% cost reduction is not a modest efficiency gain. It is a structural transformation of what the support function costs the business.

    Key Features

    Trained on Your Actual Business Logic

    Support GPT is not a generic AI that you hope will figure out your products. It is trained specifically on your documentation, your processes, your FAQs, your historical support cases. It knows how you handle refunds. It knows your SLAs. It knows what your escalation criteria are. It operates as an extension of your team — not as a separate system that needs to be told what to do in every situation.

    Multi-Channel Deployment

    Deploy across WhatsApp, Instagram, Telegram, and your website simultaneously. Customers reach you wherever they already are. The AI operates consistently across every channel, with the same quality and the same voice.

    150+ Language Support

    For international businesses, Support GPT handles multilingual conversations without custom configuration per language. Your customers communicate in their language; the system responds in kind.

    Direct CRM Integration

    Every interaction is logged directly into your CRM — structured, tagged, and searchable. Customer history is accessible to agents when escalation is required. Support data feeds into broader customer intelligence.

    Smart Escalation to Human Agents

    When an interaction genuinely requires human judgment — complex complaints, sensitive situations, edge cases outside the training scope — the system escalates cleanly, with full conversation context passed to the human agent. No customer has to repeat themselves.

    Built-In Analytics and Continuous Improvement

    The system tracks resolution rates, escalation triggers, common inquiry patterns, and response quality. This data drives continuous model improvement — the longer the system runs, the better it gets at handling your specific support volume.

    The Critical Difference: Not Scripted, Trained

    Most chatbot implementations fail because they are scripted. They handle the exact scenarios someone anticipated when building them, and fail on anything else — sending customers to dead ends or frustrating them with «I did not understand that» responses.

    Support GPT is trained, not scripted. It understands the intent behind what a customer is asking, not just the specific words they used. It can handle novel phrasings of known questions, multi-part requests, and contextual conversations that a decision-tree system would break on.

    The result is a system that customers experience as genuinely helpful — not as an obstacle they need to get past to reach a human.

    Who This Is Built For

    • E-commerce businesses with high inquiry volumes and predictable request patterns
    • Financial services companies with complex products and strict compliance requirements around communication
    • Telecoms, utilities, and subscription services where billing and account queries dominate support load
    • Healthcare and insurance operators with patient or policyholder communication at scale
    • Any business where support costs are a significant operational line item and response speed is a competitive differentiator

    See It in Action

    Explore the live demo: https://ryon-customer-support.figma.site/dashboard

    To increase support efficiency while gaining structured insight from every customer interaction, book a strategy call with Ryon.ai: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • Networking Agent: Turn Your Company’s Existing Network Into a Lead Generation Machine

    Networking Agent: Turn Your Company’s Existing Network Into a Lead Generation Machine

    Networking Agent: Turn Your Company’s Existing Network Into a Lead Generation Machine

    The Network You Are Not Using

    Every large organisation sits on a network worth millions that it is barely touching.

    Contacts accumulated over years. Former clients. Partners. Investors. Supplier relationships. LinkedIn connections across a team of 200 people. Employee networks that have never been mapped.

    Ask most companies to tell you who in their network works at a target account, and they will either spend a week manually searching or admit they simply do not know. Ask them to identify which contacts are most relevant to a new market they are entering, and you will get blank faces or an Excel file someone built three years ago.

    The network exists. The value is locked.

    Ryon’s Networking Agent unlocks it.

    What the Networking Agent Does

    The Networking Agent is a system that activates your company’s network. You upload your contacts, employee lists, partner databases, or enrich via LinkedIn — and the system makes that network queryable, searchable, and actionable through simple natural language prompts.

    Instead of searching manually, you ask:

    • Who in our network has worked at Carrefour in the last 3 years?
    • Which of our contacts are currently in a supply chain director role?
    • Who do we know at the 15 accounts we are targeting this quarter?

    The system returns ranked, relevant results in seconds — not after a week of manual cross-referencing.

    Results

    • 90% faster identification of relevant contacts

    For enterprise sales teams running account-based strategies, this is a structural advantage. The time between identifying a target account and knowing exactly who to call goes from days to seconds.

    Key Features

    Natural Language Contact Queries

    Retrieve high-value contacts instantly through plain language prompts. No search filters, no boolean operators, no exporting to spreadsheets. Ask the question and get the answer.

    Continuous Database Enrichment

    The system keeps your contact base updated and expanded — pulling new information, adding new connections, flagging outdated entries. The database gets more valuable over time, not less.

    LinkedIn Integration

    Enrich your existing contact data directly from LinkedIn — job titles, current employers, recent moves, seniority changes. The data your team has is supplemented by what is publicly available and continuously updated.

    WhatsApp, Telegram, and Slack Integration

    The Networking Agent is designed to live where your team already works. Deploy it as a WhatsApp, Telegram, or Slack integration — so querying the network is as easy as sending a message.

    150+ Language Support

    For multinational organisations, the system operates across 150+ languages without custom configuration. Your team in Tokyo and your team in Paris both get the same capability.

    Connection Request Automation

    Beyond search, the system turns your network into a consistent lead source. Automated, personalised connection request sequences — built around the right contacts at the right accounts — convert network data into pipeline.

    Full Workflow Customisation

    Every sales organisation operates differently. The Networking Agent is built to adapt to your prospecting workflows, your CRM structure, your qualification criteria — not the other way around.

    Who This Is Built For

    • Enterprise B2B sales teams running account-based go-to-market strategies
    • Business development functions looking to systematise relationship-driven outreach
    • Professional services firms where relationships are the primary commercial asset
    • Private equity and investment firms with large, complex contact networks
    • Any organisation where network leverage is a competitive advantage that is currently being left on the table

    The Problem With Manual Network Management

    Networks decay. People change jobs, change roles, change companies. A contact database that was accurate 18 months ago is significantly less useful today — and most organisations have no systematic way of keeping it current.

    Manual LinkedIn searches are slow, inconsistent, and dependent on individual effort. The knowledge of who knows whom is locked inside individual employees’ heads and LinkedIn accounts — not accessible to the organisation as a system.

    The Networking Agent makes your organisation’s collective network a structured, searchable, continuously updated asset. That is a different category of capability than what any individual employee or CRM plugin can provide.

    See It in Action

    Explore the live demo: https://ryon-networking-agent.figma.site

    To unlock the full value of your network and turn it into a structured source of opportunities, book a strategy call with Ryon.ai: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • What Customer Support Actually Costs You

    What Customer Support Actually Costs You

    What Customer Support Actually Costs You

    The Hidden Cost of Human-Only Support

    The visible cost of customer support is headcount. The invisible cost is everything around it.

    Response times that frustrate customers at 11pm when your team is offline. Inconsistency between agents: the same question, five different answers, depending on who picks up the phone. Agents spending 60% of their time on tier-one inquiries that follow identical patterns. Escalations that happen because the front-line agent did not have the right information, not because the issue was genuinely complex.

    These are not edge cases. They are the structural reality of running human-only support at scale.

    Every one of them is a cost that does not appear on a headcount report.

    Ryon’s Support GPT is built to solve all of them simultaneously.

    What Support GPT Does

    Support GPT deploys AI agents across your customer-facing communication channels: WhatsApp, Instagram, Telegram, and your website.

    These agents are trained on your company’s actual processes, documentation, support logic, and escalation criteria. Not on generic templates. On how your business actually operates.

    This is not a scripted chatbot following a decision tree. It is an AI that understands your business. It handles conversations the way your best support agent would handle them. With context, with consistency, and with the ability to adapt to each individual interaction.

    Every conversation is recorded and structured inside your admin dashboard. Full visibility into what was resolved, how it was resolved, and where human intervention was required.

    Results

    75% of all inquiries resolved with zero human involvement.

    Up to 80% reduction in customer support operating costs.

    A 75% autonomous resolution rate means 75% of all inquiries handled without a human agent ever getting involved. Not just the simple ones. The 25% that reach your team are the cases that genuinely require human judgment.

    For a 30-person support team, an 80% cost reduction is not an efficiency gain. It is a structural transformation of what the support function costs the business.

    Key Features

    Trained on Your Business, Not Generic Templates

    Support GPT is not configured with scripted responses. It is trained on your documentation, your processes, your FAQs, and your historical support cases. It knows how you handle refunds, your SLAs, and your escalation criteria. It operates as an extension of your team.

    Multi-Channel Deployment

    One deployment across WhatsApp, Instagram, Telegram, and your website simultaneously. Customers reach you wherever they already communicate. The AI operates with the same quality and the same voice across every channel.

    150 Language Support

    Multilingual conversations handled without custom configuration per language. Your customers communicate in their language. The system responds in kind.

    Direct CRM Integration

    Every interaction logged directly into your CRM. Structured, tagged, and searchable. Customer history is accessible to agents when escalation is required. Support data feeds into broader customer intelligence.

    Smart Escalation With Full Context

    When an interaction genuinely requires human judgment, the system escalates cleanly with the full conversation context passed to the agent. No customer repeats themselves.

    Built-In Analytics

    The system tracks resolution rates, escalation triggers, common inquiry patterns, and response quality. This data drives continuous improvement. The longer the system runs, the better it performs on your specific support volume.

    The Critical Difference: Trained, Not Scripted

    Most chatbot implementations fail because they are scripted. They handle the exact scenarios someone anticipated when building them and break on anything else.

    Support GPT understands intent, not just keywords. It handles novel phrasings of known questions, multi-part requests, and contextual conversations that a decision-tree system cannot process.

    The result: customers experience it as genuinely helpful. Not as an obstacle to get past before reaching a human.

    Who This Is Built For

      • E-commerce businesses with high inquiry volumes and predictable request patterns
      • Financial services with complex products and strict communication requirements
      • Telecoms, utilities, and subscription services where billing and account queries dominate support
      • Healthcare and insurance operators with patient or policyholder communication at scale
      • Any business where support costs are a significant operational line item and response speed is a competitive differentiator

    See It in Action

    Live demo: ryon-customer-support.figma.site/dashboard

    Book a strategy call: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • How We Built Agent-to-Agent Communication Infrastructure in One Night

    How We Built Agent-to-Agent Communication Infrastructure in One Night

    How We Built Agent-to-Agent Communication Infrastructure in One Night

    The Problem We Could Not Ignore

    We had been building AI systems for two years. Call center summarizers, executive copilots, infohubs that let you query your entire business with natural language. Every one of them was a standalone agent.

    They were powerful. But they could not talk to each other.

    Every time we needed two agents to collaborate, we built a one-off bridge. Custom webhooks. Shared message queues. Sometimes just a database table both agents would poll. It worked, but it was fragile, non-reusable, and impossible to explain to a client.

    One night I decided to fix this properly.

    The Design Constraint

    The rule was simple: if your agent can make an HTTP call, it can communicate with any other agent.

    No SDKs. No new protocols. No dependencies beyond Express. Just a neutral relay that any agent, written in any language, running on any platform, could use.

    What We Built

    AgentRelay is a lightweight Node.js service with three core primitives:

    Register: — any agent announces itself with a name and optional webhook URL. Gets back a unique agentId.

    Send: — send a message from one agent to another by ID. Message is stored and, if the recipient has a webhook, delivered immediately.

    Poll: — check for new messages. Returns unread messages and marks them as read.

    That is the entire protocol.

    The Build

    Claude Code shipped the initial server in under an hour. Seven endpoints, in-memory storage, working health check.

    We then added the landing page: starfield background, green accents, macOS-style code blocks. It looked like a real product.

    The production upgrade came next:

    — SQLite persistence (data survives restarts)
    — Rate limiting via express-rate-limit
    — 24-hour TTL cleanup for inactive agents
    — Message cap of 500 unread per inbox
    — Admin dashboard at
    — Join notification webhooks
    — Uptime reporting in

    Total: about 400 lines of clean Node.js.

    The Test

    We registered two agents via curl. One was our research agent (Ryon). One was a simulated external agent (Nassistant).

    Ryon sent a message:

    Nassistant polled its inbox, found the message, and replied.

    Real agent-to-agent communication. No human in the loop after the initial registration.

    What This Enables

    The immediate use case is multi-agent workflows. A coordinator agent breaks a task into subtasks and delegates to specialist agents. Each specialist sends results back through the relay. The coordinator assembles the final output.

    The longer term vision: a public relay at relay.ryon.ai where any AI agent can register and discover other agents. An agent directory. A communication substrate for the open agent ecosystem.

    The Broader Point

    This project took one night. Not because it is trivial — agent communication infrastructure matters enormously — but because we had the right tools and constraints.

    The constraint was: make it as simple as possible. Three endpoints. No auth. curl-friendly.

    The tool was Claude Code, which built, iterated, and tested without needing hand-holding.

    This is what AI-assisted infrastructure development looks like in 2026. You describe the problem clearly, set the constraints, and the agent builds it while you sleep.

    The bottleneck is no longer writing the code. It is knowing what to build and why.

    Artem Techman is co-founder of Ryon.ai, an AI integration agency that builds intelligence layers for enterprise clients. AgentRelay is open source and available at relay.ryon.ai (coming soon).

  • Executive CoPilot: The AI Assistant That Integrates Into Your Business and Runs It With You

    Executive CoPilot: The AI Assistant That Integrates Into Your Business and Runs It With You

    Executive CoPilot: The AI Assistant That Integrates Into Your Business and Runs It With You

    The People Who Need to Make Decisions Are Buried in Tasks That Do Not Require Them

    Every large organisation has this problem.

    The executives and operators who carry the most responsibility are the ones spending the most time on tasks that should not require their judgment.

    Searching internal systems for information that should take 10 seconds. Drafting reports that aggregate data someone else already compiled. Scheduling meetings across time zones. Writing emails that follow the same structure they have followed for three years.

    This is not a performance problem. It is a systems problem. The tools organisations have built do not automate execution. They just store records of it.

    Ryon’s Executive CoPilot closes the gap.

    What the Executive CoPilot Does

    The Executive CoPilot is an enterprise AI assistant that integrates directly into your existing internal systems. Your CRM, ERP, document management platform, and communication tools.

    This is not a chatbot you paste information into from the outside. It has direct access to your systems. It reads your live data, executes tasks within your workflows, and surfaces the right information at the right moment.

    Core functions it handles from day one:

    Instant information retrieval. Ask any question about your business data and get an answer in seconds. Not hours.

    Document generation. Contracts, reports, proposals, and briefs generated from your templates and your live data. Not from scratch.

    Email drafting. Context-aware drafts built on prior conversation history and your established communication patterns.

    Meeting scheduling. End-to-end coordination across calendars, time zones, and availability without anyone chasing anyone.

    Recurring reporting. Reports assembled from live system data and delivered on schedule. No manual aggregation.

    Results

    80% reduction in manual repetitive tasks.

    90% faster information retrieval across internal systems.

    90% faster document and email generation.

    These are not efficiency improvements at the margin. They are structural changes to how your teams operate, freeing leadership from execution overhead so they can focus on decisions that actually require them.

    Key Features

    Direct Integration With Your Existing Stack

    The Executive CoPilot connects to the systems you already operate. No data migration. No infrastructure changes. No new platforms to manage. It becomes a capability layer on top of what you have.

    Role-Based Access and Configuration

    Different roles need different capabilities. A CFO gets financial data and reporting. A sales director gets pipeline and CRM access. An operations lead gets logistics and fulfilment visibility. Every deployment is configured to how each function actually works.

    Custom Skills That Expand Over Time

    The initial deployment covers your highest-frequency repetitive tasks. As the system learns your workflows, new skills are added continuously. Teams shift from manual execution to oversight of automated execution.

    Enterprise Security Standards

    Full data traceability, role-gated access, audit logs, and compliance with your infrastructure team’s requirements. The CoPilot operates inside your environment, not outside it.

    Who This Is Built For

    The Executive CoPilot creates the most value for:

      • C-suite executives who need faster access to business intelligence without analyst dependency
      • Operations teams carrying high volumes of recurring process execution
      • Sales and account management functions with heavy CRM and communication workloads
      • Finance teams producing recurring reports from multiple data sources
      • Any organisation where skilled people are spending skilled-people time on tasks that should be automated

    The Department as a Service Model

    Ryon deploys the Executive CoPilot on a retainer basis.

    This is not a software licence. It is an ongoing operational partnership: initial integration, custom skill development, continuous optimisation, and expansion of capability coverage as your needs evolve.

    You are not buying a product. You are acquiring a function that keeps getting more capable over time.

    See It in Action

    Live demo: https://ryon-executive-copilot.figma.site

    Book a strategy call to see what this looks like inside your organisation: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • Infohub: Real-Time Business Intelligence Without Dashboards, Delays, or Manual Reports

    Infohub: Real-Time Business Intelligence Without Dashboards, Delays, or Manual Reports

    Infohub: Real-Time Business Intelligence Without Dashboards, Delays, or Manual Reports

    The Visibility Problem Every Large Organisation Has

    Ask a CEO of a 1,000-person company what their best-performing region is this quarter. Most cannot tell you without making two phone calls and waiting 24 hours for someone to pull a report.

    This is not because the data does not exist. It exists — in the ERP, in the CRM, in the logistics platform, in the finance system. The problem is that no one has built a single way to see it all at once, in real time, without going through an analyst.

    And so decisions get made on week-old data. Opportunities get missed because the visibility gap was just wide enough. And the analyst team spends 40 hours a week producing reports that were already obsolete when they were written.

    Infohub is built to eliminate that gap.

    What Infohub Does

    Infohub connects to your existing systems — ERP, CRM, logistics, finance, HR — and creates a live, structured view of your entire business that you can query in plain language.

    No dashboards to maintain. No waiting for reports. No intermediary.

    Ask: What are our top-selling SKUs in the northeast region this month compared to last year?

    Get an answer in seconds — not tomorrow morning.

    Ask: Which suppliers are running late on delivery and what is the downstream impact on fulfilment?

    Get the answer, the context, and the recommended action.

    That is not a BI tool. That is business intelligence that actually behaves like intelligence.

    Results

      • 90% faster access to critical business information
      • 90% reduction in reporting time

    For a company spending 40 analyst hours per week on reporting, a 90% reduction is 36 hours per week returned to higher-value work. For leadership, it means decisions made on real-time data instead of last week’s extract.

    Core Capabilities

    Natural Language Queries Across All Systems

    Infohub understands questions the way a business leader would ask them — not structured SQL, not filter dropdowns. You ask in plain language and get structured, sourced answers.

    Connects to Your Existing Stack

    Infohub works with your current ERP, CRM, and data systems. No infrastructure changes required. It connects via API and connector layers to the systems you already operate — typically in 6-8 weeks from first engagement.

    Built for Complex, Data-Heavy Organisations

    Infohub is designed specifically for organisations where data is distributed across multiple systems, multiple regions, and multiple formats. The more complex your data landscape, the more value it creates.

    Real-Time Sync

    Critical KPIs are refreshed continuously. Leadership does not see last night’s extract — they see what is happening now.

    Role-Based Access

    Every user sees what they need to see. A regional director sees their region. A category manager sees their category. The CFO sees the full P&L. Access is configured by role, not by who knows the right person to ask.

    Proactive Alerts

    Infohub does not wait to be asked. When stock reaches a risk threshold, when a revenue metric deviates from plan, when a supplier SLA is at risk — the system flags it proactively. You find out before it becomes a problem, not after.

    From Data to Clarity

    Most large organisations do not lack data. They lack the ability to see it.

    Data is distributed, siloed, formatted inconsistently across dozens of systems that were never designed to talk to each other. The result: leadership operates on approximations, summaries, and instinct — not on the actual state of the business.

    Infohub is not a reporting tool. It is an intelligence layer — a way of seeing your entire business as it is, not as it was when someone last ran a query.

    Deployment Timeline

    Typical deployment from first discovery call to full system live: 6-8 weeks.

    There is no data migration. No replacement of existing systems. Infohub connects to what you have. The only thing that changes is your ability to see it.

    Who This Is Built For

      • Large enterprises where data is spread across multiple platforms and visibility requires analyst intervention
      • Retail and distribution businesses managing inventory, sales, and logistics across multiple regions
      • Financial services organisations needing real-time portfolio and operational visibility
      • Manufacturing and supply chain businesses where speed of information directly affects operational decisions
      • Any C-suite that is currently dependent on a weekly report to understand what is happening in their business

    See It in Action

    Explore the live demo: https://ryon-infohub.figma.site

    If you want to eliminate reporting bottlenecks and gain real-time visibility across your business, book a strategy session with Ryon.ai: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai

  • AI Call Center Summariser: Automate Every Call Summary, Eliminate Manual Notes

    AI Call Center Summariser: Automate Every Call Summary, Eliminate Manual Notes

    AI Call Center Summariser: Automate Every Call Summary, Eliminate Manual Notes

    Every Call Ends the Same Way, and It Is Costing You More Than You Think

    The call ends. The customer hangs up. Your agent switches windows and spends the next 5 to 10 minutes writing notes.

    Across a 50-agent call center operating at volume, that is not a minor inconvenience. It is a structural drag on your entire operation. Calls your agents never made. Revenue you never tracked. Data that goes into your CRM in 50 different formats depending on who wrote it.

    The average call center agent spends 20 to 30% of their working day on post-call documentation. That is time that could be calls. It is also time that produces rushed, inconsistent, incomplete records, which means the CRM data you rely on for decisions is built on a foundation you cannot fully trust.

    Ryon’s Call Center Summariser was built to close this gap completely.

    What the Call Center Summariser Does

    The Call Center Summariser is a middleware layer that connects your telephony system to your CRM and automates everything in between.

    It does not replace your telephony. It does not replace your CRM. It connects them.

    The moment a call ends:

    The conversation is automatically transcribed. An AI summary is generated: structured, consistent, and accurate to the content of the call. Key data is extracted: customer intent, action items, sentiment score, escalation flags. Everything is pushed directly into your CRM in the right format, in the right fields.

    No manual input from the agent. No delay. No missed details. No inconsistent formatting.

    The agent moves immediately to the next call.

    Results That Change Operational Math

    20% increase in daily call capacity.

    90% reduction in manual summarisation effort.

    At scale, a 20% increase in call capacity across a 50-agent team is the equivalent of hiring 10 additional agents without adding to headcount.

    A 90% reduction in post-call admin across a team spending 2 hours per shift on documentation is 1 hour 48 minutes returned to calling, every agent, every shift.

    Key Features

    Works With Your Existing Stack

    The Call Center Summariser integrates with any telephony system and any CRM your business currently uses. No infrastructure migration. No replacing existing tools. It connects on top of what you already have.

    150 Language Support

    Multilingual call centers handled without custom configuration. French, Arabic, Mandarin, and 147 other languages. Transcription and summarisation quality remains consistent regardless of language.

    Agent Performance Analytics

    Beyond individual call summaries, the system generates analytics across all calls: average handle time, resolution rates, common escalation triggers, and sentiment trends over time. Managers get structured visibility that previously required manual compilation.

    Flexible, Usage-Based Billing

    Charged on hourly usage. No large upfront licences. No per-seat pricing that penalises growth. You pay for what you use, with full flexibility to scale up or down.

    Full Technical Customisation

    Custom extraction fields, custom summary formats, custom CRM mapping. Built to fit your operation precisely, not the other way around.

    Who This Is Built For

    The Call Center Summariser delivers the most value to:

    — High-volume B2C call centers where throughput directly maps to revenue

    — Enterprise sales teams that need structured, consistent CRM data from every customer interaction

    — Financial services and insurance where compliance documentation is mandatory on every call

    — Telecoms, utilities, and logistics operators with large, distributed agent teams

    — Any organisation where agents currently spend meaningful time writing notes after calls

    Why This Is Not Just Another Transcription Tool

    Generic transcription tools give you a text file. The Call Center Summariser gives you an outcome.

    The difference is the intelligence layer between the transcript and your CRM: structured extraction, contextual summarisation, direct integration with your existing systems, and analytics that aggregate patterns across thousands of conversations.

    You are not buying a transcription tool. You are buying back 20 to 30% of your agents’ productive time and converting it into calls, revenue, and CRM data you can actually trust.

    See It in Action

    Live demo: https://ryon-call-center-summariser-analytics.figma.site

    Book a strategy call to see what this looks like on your call volumes: artem@ryon.ai | +33 7 77 72 26 23 | ryon.ai