For

Book a scoping call
System Integration

AI Systems Integration Services

Wire AI agents and RAG pipelines into the systems you already run — auditable data flows, not a bolt-on chatbot.

Book a scoping callSee our work

Most AI features never make it past the demo because they were never wired into anything. A support agent that can't read the actual ticket, an assistant that can't write back to the CRM, an automation somebody has to re-trigger by hand because it can't reach the system it's supposed to update — the model works, and the integration doesn't exist.

We build the connective layer: LLM agents and RAG pipelines that read and write through the APIs, webhooks, and databases your team already runs. Tenant isolation is enforced at the data layer, not asserted in a README, and every write path sits behind the same grounding guard we use everywhere else, so an agent can't act on a number it invented.

That integration work moves fast because it's disciplined, not because it's rushed: senior architects with AI leverage, every deviation from the integration spec recorded as a numbered ADR, so what got built and why is never a mystery six months later.

The problem we solve

AI pilots that stall at proof-of-concept because nobody connected them to the systems of record — the CRM, the ticketing queue, the internal API — the business actually runs on. The model works in isolation and does nothing in production.

What you get

Read/write integration with your CRM, ticketing, ERP, or internal APIs — not a read-only chatbot
Tenant isolation enforced at the data layer with Postgres RLS, not app-layer checks
Grounding guard on every write path — an agent can't act on a number it invented
Works with modern REST/GraphQL APIs and legacy systems without a modern API surface
Webhook and event-driven triggers so agents react to your systems in real time
Provider-agnostic model layer — swap providers without touching the integration code

What we deliver

  • Integration architecture and data-flow map covering every system touched
  • Production integration layer deployed to your infrastructure
  • Numbered ADRs recording every architectural decision and deviation
  • Isolation and security review before handover
  • Runbook, monitoring, and 30-day warranty

Who it's for

  • Teams with an AI pilot that never got wired into the CRM, ticketing, or internal APIs it needs to act on
  • Companies running LLM agents that need to read and write against systems of record, not just chat
  • Regulated teams needing agent write-paths a compliance review can trace

Indicative investment

Transparent ranges so you can plan. Final scope and quote are confirmed on your scoping call.

PackageFromTimeline
AI Integration — Single System$3,5002–4 weeks
AI Integration — Multi-System$7,0004–8 weeks
Enterprise Integration Suite$16,0008–12 weeks

Related work

Waste Management / IoT

Artemis — Smart Waste Management Platform

From manual rounds to real-time monitoring across the fleet

Retail / Inventory Management

StockSense — Inventory Management System

Real-time stock visibility with low-inventory alerts and purchase-order tracking, built to catch stockouts before they happen

E-Commerce / SaaS

Orders & Subscription Management System

Fully automated subscription lifecycle management from sign-up to renewal

Frequently asked questions

How much does it cost to integrate AI into our existing systems?

A single-system integration — wiring one agent or RAG pipeline into one system of record — starts at $3,500 and runs 2–4 weeks. Multi-system integrations connecting three or more start at $7,000 (4–8 weeks), and enterprise suites connecting six or more start at $16,000 (8–12 weeks). Final cost depends on how many systems are touched and whether each exposes a usable API.

Can you integrate with a system that doesn't have a modern API?

Often, yes. We integrate through REST and GraphQL APIs where they exist, and fall back to database-level integration, file-based sync, or a middleware layer for legacy systems that don't expose one. The isolation and grounding guarantees apply regardless of which integration path a given system requires.

Will the AI be able to write back to our systems, or just read from them?

Both, when the use case calls for it. Every write path sits behind the same grounding guard used across all our engineering: an agent cannot act on a number the deterministic layer didn't produce. Read-only integrations are simpler and ship faster; write-capable ones get the full security review before going live.

How do you handle authentication and access control across our tools?

We integrate with your existing identity provider and enforce tenant isolation at the data layer with Postgres row-level security, not with checks in the UI. The integration layer only holds credentials scoped to what it needs, and every access path is covered in the security review before handover.

How is this different from a POS or payroll integration?

It's a different problem. We're not syncing point-of-sale or payroll data between two systems of record — we're wiring an AI agent or RAG pipeline into the APIs, databases, and internal tools your team already runs, so it can act inside your actual infrastructure instead of sitting beside it as a separate tool.

Ready to scope your system integration project?

Start with a scoping call. You leave knowing the timeline, the fixed price, and whether it's a fit — before you commit to anything.

Book a scoping call