NEXT-GEN AI INFRASTRUCTUREProduction Ready

Autonomous AI agents and MCP architecture for your business

We do not build script-based chatbots. We deploy digital departments on MCP architecture—standalone or integrated with your CRM stack—cutting API spend by up to 70%.

live data flow
CRM / Request
MCP Orchestrator
Local utilities
Knowledge base (RAG)

// SOLUTIONS

Service matrix

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We work with your stack and CRM systems

AmoCRMBitrix24SalesforceMicrosoft Dynamics 365Oracle NetSuite CRMZoho CRMCreatio1C:EnterpriseTelegram APIWhatsApp BusinessYandex CloudAmoCRMBitrix24SalesforceMicrosoft Dynamics 365Oracle NetSuite CRMZoho CRMCreatio1C:EnterpriseTelegram APIWhatsApp BusinessYandex CloudAmoCRMBitrix24SalesforceMicrosoft Dynamics 365Oracle NetSuite CRMZoho CRMCreatio1C:EnterpriseTelegram APIWhatsApp BusinessYandex Cloud
System Architecture

Autonomous agent system graph

Hover over any module to trace reasoning routes and token flow in real time.

ENGINE // CORECORE ROUTING ENGINE

The main FastMCP-based routing node distributes business tasks and coordinates all connected system modules.

MOD // CRMCRM INTELLIGENCE CONTOUR

Autonomous business process management, instant parsing of inbound client requests, and automatic deal progression inside your CRM systems.

AUTOMATIONLEAD PROCESSINGPIPELINE CONTROL
MOD // DATAKNOWLEDGE & CONTEXT BASE

An isolated data store tailored to your requirements, giving agents accurate company context.

CONTEXT RECALLDATA INTEGRATIONSECURE STORAGE
MOD // SWARMMULTI-AGENT SWARM

A coordination network of specialized AI agents where each node is optimized for its role and can flexibly combine with others into a single team.

TEAM WORKFLOWROLE EXECUTIONEFFICIENT SWARM
INBOUND DATA(Triggers, Events & Messages)
TARGET ACTIONS(System updates, Outputs & Results)

// Architecture layers

Engineering technology stack

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// Cooperation stages

How we launch your AI agent

A transparent engineering process — from the first audit to scaling your digital department without unnecessary bureaucracy.

01

Process audit

We study your CRM, sales funnels, and operational bottlenecks to identify where an autonomous agent delivers maximum impact.

02

MCP architecture design

We define the agent graph, integration points, and action scenarios. We select models and stack to match your requirements.

03

MVP development

We build a working prototype in 14 days: agents, RAG memory, AmoCRM / Bitrix24 integration, and hypothesis testing.

04

Deployment

We deploy the solution in your infrastructure, connect CRM, and train your team to work with the digital employee.

05

Support & growth

We scale the agent network, add new scenarios, and support the system at every stage of growth.

// ROI calculator

How much you save with AI

1,000
$4,000

Reduction in staff costs

$1,568/mo

Token savings

up to 53%

Payback period

112 days

* Calculation includes lead volume, current manager payroll, and estimated MCP infrastructure cost for your flow.

// FAQ

Answers about AI agents and MCP architecture

What is HEXPOINT?

HEXPOINT is an engineering AI team that designs and deploys autonomous AI agents on MCP architecture (Model Context Protocol). We integrate digital employees into AmoCRM, Bitrix24, Salesforce, and other CRM systems.

How are MCP agents different from regular chatbots?

Chatbots reply to messages using scripts. MCP agents act autonomously: they receive CRM events, query corporate knowledge bases (RAG), call tools, and execute business actions — moving deals, updating records, and routing tasks.

Which CRM systems do you integrate with?

We integrate with AmoCRM, Bitrix24, Salesforce, Microsoft Dynamics 365, Oracle NetSuite CRM, Zoho CRM, Creatio, 1C:Enterprise, plus Telegram, WhatsApp Business, and cloud infrastructure.

How fast can you launch an MVP?

A typical MVP with working agents, RAG memory, and CRM integration is delivered in 14 days: audit, MCP graph design, prototype development, and hypothesis testing.

How much can API and operational costs be reduced?

MCP architecture routes requests through local utilities and contextual caching, reducing LLM API spend by up to 70% compared to direct unorchestrated API calls.

Can the solution be deployed on-premise?

Yes. We deploy the agent network in isolated client infrastructure — Docker, local LLMs, secure API bridges — for full control over trade secrets and data residency.