Services/AI implementation & integration

Capability

AI implementation & integration

Wire AI into the stack you already run.

APIs, data paths, auth, and production hardening so model calls become product behaviour, not a side demo.

What we build

The engineering pieces included under this capability.

01

System fit

CRM, ERP, support tools, and internal APIs connected with clear contracts.

02

API layer

Stable interfaces so product teams call AI without owning the model stack.

03

Data paths

Secure movement of context in and results out, with retention rules.

04

Security basics

Secrets, least privilege, audit logs, and deployment constraints.

05

Ops hooks

Latency, error, cost, and quality signals for production monitoring.

Example use cases

Concrete jobs this capability is built for. Not a full project proposal.

01

AI inside your CRM

Surface account insights and suggested next actions inside Salesforce or HubSpot, without a separate AI tool.

02

Smarter ticket routing

Classify intent from the ticket text and customer history, then send it to the right queue with context attached.

03

Back-office document flow

Extract fields from incoming documents, validate them, and post clean results into finance or ops systems.

Build path

  1. 01

    Integration map

    Systems, auth, data constraints, and success metrics.

  2. 02

    Thin vertical

    One path end to end before expanding coverage.

  3. 03

    Harden

    Rate limits, fallbacks, monitoring, and handoff docs.

Typical stack

Integration

REST / webhooksevent busesqueue workers

Platform

PythonTypeScriptPostgreSQLcloud of choice

Models

OpenAIAnthropicvendor-neutral routing

Need this in production?

Bring the use case and constraints. We will say if a sprint or pilot fits.

Book a 2-week architecture sprint