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AI Engineering

AI built into the platform, not bolted on: MCP servers that give assistants safe, permissioned access to a product's data and actions, agent pipelines that draft, review and publish behind human approval gates, and integrations with the model providers the use case actually needs. An AI client is treated like any other client of the backend, authenticated, scoped and audited. The proof point is a live MCP server running in production against a real platform.

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AI Engineering
4 months
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AI Engineering - MCP Servers and a Cross-Provider Memory Hub

Assistants forget between sessions, and each provider keeps its history in its own shape, so knowledge earned in one conversation is unavailable in the next. We built the plumbing that fixes it: MCP servers that expose knowledge, content and tools to any assistant, and a memory hub that normalises sessions from several providers into one queryable store. None of the hard problems here were prompt problems. They were system problems: schema design across incompatible session formats, isolation between scopes, tool safety, and an approval model for anything that writes. It runs on self-hosted hardware, so nothing leaves the building.

FullTime
Onsite
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Md Moniruzzaman

Services You May Also Need

App Development

The platform's apps, wherever the users work: React Native and Expo for iOS and Android, shipped through both stores, and Electron with React for the work that lives on the desktop, offline-ready and packaged for Windows, macOS and Linux. The app is never a separate product, it is a surface of the platform, wired to the same backend, auth and data model as every other client and released on the same cadence.

Website Development

Web frontends built on React, Next.js and Tailwind against a headless CMS: server-rendered, localized, structured for search engines and AI crawlers alike. The same discipline whether it is a marketing site or the web face of a multi-tenant platform: performance measured, content modelled, deploys automated.

DevOps Engineering

The infrastructure underneath the platforms: Kubernetes clusters on owned or cloud hardware, Dockerized services, CI/CD that ships on push, automated TLS, monitoring, scheduled backups and zero-downtime cutovers. The proof point is a production migration off managed cloud with no minute of downtime recorded.

Startup Development

A platform taken from architecture to first customers: the data model, the backend, the surfaces, the deploy pipeline and the operating discipline, scoped so the MVP is a thin slice of the real system rather than a throwaway. Built to survive the growth it is hoping for.

Additional Services

The work around the platform: UI/UX design, headless CMS builds on Strapi, integrations with third-party APIs, architecture reviews and pre-build technical scoping. Smaller pieces, held to the same standard, because they are what keeps a platform coherent.