AI That Works Inside Your Existing Systems
An AI system that cannot read your data or act in your systems is a demo, not a business tool. We build the integration layer that connects AI reasoning to the technology your business already depends on.
From CRM and ERP to help desk, communication platforms and data warehouses — we connect AI to your existing technology environment so it becomes part of how work actually happens.
The Difference Between Isolated AI and Integrated AI
The gap between AI that impresses in a demo and AI that changes how work gets done is usually an integration problem.
AI as an isolated app
Your team asks AI questions in a separate tool. They manually copy answers back into the systems where work happens. The AI has no access to current data.
AI inside your workflow
AI is accessible from within Slack, your CRM or your help desk. It reads your actual data, takes action in your systems and produces results where your team already works.
What We Connect
Eight categories of business system we integrate with AI — covering the full range of where your data and workflows live.
CRM & Sales
AI connected to your customer data — enriching records, qualifying leads, generating summaries and surfacing insights within your existing sales workflow.
ERP & Finance
AI access to operational and financial data — automating reconciliation, processing invoices and surfacing anomalies without leaving your ERP environment.
Communication Platforms
AI agents and workflows delivered through the communication tools your teams already use — no new interfaces, no context switching.
Productivity Suites
AI connected to your documents, calendars, emails and collaborative tools — making existing content searchable, actionable and intelligent.
Help Desk & Support
AI that reads your ticket history, knows your product and resolves routine queries — integrated directly into your support platform and escalation workflow.
Data & Databases
AI connected to your data warehouse and operational databases — enabling natural language querying, anomaly detection and automated reporting.
Document Platforms
AI access to your document repositories — with permission-aware retrieval, document intelligence and search across all your business content.
Custom & Internal APIs
Integration with internal systems that have no off-the-shelf connector — built through API analysis, reverse engineering and custom adapter development.
Integration Architecture, Layer by Layer
How AI connects to existing systems — from your current technology through to business action.
Existing Systems
Your existing technology — unchangedCRM, ERP, help desk, productivity suites, databases, document stores
API & MCP Layer
Integration and authenticationSecure, authenticated connections to each system. Read and write access scoped to minimum required permissions.
AI Reasoning Layer
Intelligence layerLanguage model reasoning over retrieved context. Classification, generation, summarisation and decision support.
Agent / Automation Layer
Action and orchestrationAgents and workflows that orchestrate multi-step tasks using both the AI and system layers.
Business Action
Real business impactCommitted outcomes: records updated, messages sent, approvals triggered, data written to systems of record.
The Model Context Protocol: Agent-Grade Integration
MCP (Model Context Protocol) is the standard for giving AI models structured, authenticated access to external tools and data sources. It is how agents move from reasoning about information to acting on it.
Where MCP is not available — for legacy systems, custom platforms or proprietary APIs — we build the integration layer directly, exposing capabilities to the AI in a standardised and auditable way.
The result is AI that can read your Salesforce records, query your database, send a Slack message, update a Google Sheet and trigger an approval workflow — as part of a single coherent workflow.
Standardised tool definitions for AI models to call business systems
Secure, scoped authentication for each connected system
Read and write access where needed — read-only where not
Composable — multiple MCP servers combine into a unified agent capability
Works with Claude, OpenAI and other leading models
Auditable — every call logged with context and outcome
Security by design
Every system connection uses minimum-required permissions. Credentials are stored securely and rotated. All AI access to business systems is logged and auditable.
What an Integration Engagement Delivers
Integration architecture document
A clear map of what connects to what, how authentication works and what data flows in each direction.
Secure, scoped connectors
Each system connection built with minimum-required permissions, credential management and access controls.
Tested integration layer
Every connector tested for the success case, error cases and edge cases before deployment.
Monitoring and observability
Logging, alerting and dashboards so you know when integrations are working and when they are not.
Operational documentation
Runbooks for managing credentials, handling errors and extending integrations with new systems.
Ongoing integration support
Systems change. We provide support for integration maintenance as your technology environment evolves.
Which Systems Do You Need AI Connected To?
Tell us what systems you operate and what you want AI to be able to do with them. We will map out a realistic integration architecture and explain what it takes to build it.