AI & Claude integration
Connect AI to the systems your business already runs on — securely, auditably, and in production.
- MCP servers
- Agent workflows
- Guardrails
Backend services in C# and Node.js. Interfaces in React and Angular. Cloud that stays up. And when you're ready — AI agents wired into all of it, safely.
End-to-end engineering services for organisations that need their software to work, scale, and now — talk to AI.
Connect AI to the systems your business already runs on — securely, auditably, and in production.
Services and APIs built on .NET and Node.js — designed for load, versioning, and change.
AWS and Azure architecture, containerised deployment, and CI/CD pipelines your team can run.
Framework migrations and re-platforming done incrementally, without stopping the business.
SQL Server optimisation, EF Core done right, data lineage, and pipelines that stay correct.
Web applications in React, Angular, and Blazor — plus Office.js add-ins and internal tools.
Domain patterns we understand well enough to be useful from the first week.
Calculation engines, policy and rating workflows, and audit-heavy integration.
Work queues, scheduling systems, and integration between plant and platform.
Multi-tenant platforms, usage metering, and AI capability built into products.
Catalogue, order, and fulfilment integration across storefront and back office.
Document workflows, reporting automation, and the internal tools firms run on.
Tier-2 and tier-3 market businesses ready for systems metros take for granted.
Your work is done by the architect you spoke to — not handed down a bench.
Fourteen years of running systems where downtime is expensive shapes every decision.
Honest estimates, visible progress, and a clear "no" when something isn't worth building.
Documentation and knowledge transfer are part of the work, not an afterthought.
Order matters here — each step exists to make the next one cheaper.
What systems exist, who owns them, and where the data actually lives. Usually a week, sometimes less.
One narrow slice, end to end, against real data. If it doesn't work here, it won't work at scale.
Auth, rate limits, logging, cost controls, and the failure paths nobody enjoys writing.
Documentation and a walkthrough for your team. The goal is that you don't need us afterwards.
A defined deliverable, a defined price, a defined date. Best when the problem is already well understood.
Fits: integrations, add-ins, migrationsOngoing senior engineering capacity embedded with your team, billed monthly, with a short notice period.
Fits: product teams, long-running platformsReviews, roadmaps, and AI-readiness assessments — a senior second opinion before you commit budget.
Fits: CTOs, engineering leadsPractical writing on the problems we work on — the things we'd tell you on a call, written down.
Enterprise AI projects don't fail at the model — they fail at the seam. What the integration layer actually consists of, and how to build it.
Read the article → ModernisationWhat production actually does, why data moves before code, and why slices beat big bangs.
Read the article →Founder & Principal Architect
Fourteen years building and running production software — enterprise platforms, cloud infrastructure, and the integration work that holds them together. Most of that time spent on systems where downtime is expensive and the data has to be right.
Teleia exists because that experience matters more, not less, once AI is involved. The hard part of AI in an enterprise isn't the prompt — it's everything the prompt has to touch.
A short description of the system and the problem is enough to start. If it isn't something we should take on, we'll say so.
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