What we build
What this service covers, in detail.
Well-designed APIs, third-party integrations, webhooks, MCP servers and developer portals.
- 01
REST APIs
Resource-oriented, versioned APIs with consistent errors, pagination and idempotency.
- 02
API gateways
Authentication, rate limiting, routing and observability at a single, well-governed entry point.
- 03
Third-party integrations
Connectors for CRMs, ERPs, payment, shipping and marketing tools built to survive vendor changes.
- 04
Webhooks
Signed delivery with retries, replay and a console so customers can debug their side.
- 05
OAuth integrations
Secure authorization flows with token storage, refresh and revocation handled properly.
- 06
Background processing
Queues and workers for long-running jobs with back-pressure and dead-letter handling.
- 07
Data synchronisation
Incremental, conflict-aware sync with reconciliation to prove records match.
- 08
Developer portals
Interactive documentation, API keys, sandboxes and sample clients.
- 09
MCP servers
Model Context Protocol servers that expose your systems to AI agents safely, with scoped permissions.
- 10
AI service integrations
Wrap model providers behind internal APIs with caching, quotas and observability.
- 11
Usage metering and monitoring
Per-customer analytics on requests, errors and latency that feed billing and support.
Example use cases
Where teams put this to work.
- 01
Public or partner API
Turn internal capabilities into a stable product with documentation and keys.
- 02
ERP to storefront sync
Keep stock, prices and orders aligned between the commerce site and back office.
- 03
Expose systems to AI agents
Publish an MCP server so assistants can perform approved actions.
- 04
Legacy connectivity
Place modern APIs in front of systems that only offer files or databases.
Technical approach
Tools we typically use here.
A starting point, not a mandate. We adapt to your existing stack and constraints.
- TypeScript
- Node.js
- Python
- FastAPI
- OpenAPI
- GraphQL
- Redis / queues
- PostgreSQL
- OAuth 2.0
- MCP
How it works
The engagement, step by step.
- 1
Map flows and ownership
Which system owns which record, and what happens when they disagree.
- 2
Design the contract
Endpoints, payloads and error behaviour agreed and documented before code.
- 3
Build resilient workers
Idempotency, retries and back-pressure so bad hours never corrupt data.
- 4
Reconcile and verify
Automated comparison against source systems.
- 5
Monitor and own
Alerts, runbooks and a named owner per integration.
FAQ
Frequently asked questions
REST or GraphQL?
REST suits most partner APIs for simplicity. GraphQL helps when many clients need flexible reads. We recommend per case.
What if a third-party API goes down?
Requests queue and retry with back-off, alerts fire at thresholds, and data is delayed rather than lost.
What is an MCP server?
A standard way to expose tools and data to AI applications. We build them with scoped permissions and audit logs.
Projects
Reference projects that show this in practice.
Systems we designed as demonstrations, using sample data. Each has features, architecture and security notes.
Related capabilities
Often combined with
AI Engineering
Agentic systems, LLM-powered applications and enterprise assistants engineered with evaluation, security and oversight.
Enterprise Software Development
CRM, ERP, HR, portals and operational systems designed around how your organisation works.
SaaS & Product Development
Multi-tenant SaaS platforms with workspaces, billing, permissions and the admin tooling to run them.
Planning a API & Integration Engineering project?
Tell us the problem you are solving. We will reply with questions, options and a realistic next step.