Put AI inside the product, where it earns its keep.
Algoramming integrates AI and machine learning into software from Dhaka, Bangladesh for teams across the UAE, Qatar, Saudi Arabia, the US, the UK, and Australia. We build features on top of large language models and, where it fits, custom models, with the retrieval, guardrails, and evaluation that make AI dependable in production rather than impressive only in a demo.
We build AI features into your product, on top of the right models, with the retrieval, guardrails, and evaluation that separate something dependable from a clever demo.
What this specialism means in practice, written for the people who buy it and the people who will live inside the product after launch.
Almost anything looks impressive in a first demo with a capable model. Production is where AI features earn or lose trust. The hard, valuable work is grounding answers in your own data through retrieval, designing prompts and guardrails so the system fails safely, and controlling cost and latency so the feature is affordable at scale. We build for that reality, so the AI holds up on the messy, real inputs your users will actually throw at it.
AI features are probabilistic, which means quality is a distribution, not a yes or no. We build an evaluation harness for the behaviour that matters, so you can see how often the system is right, where it goes wrong, and whether a prompt or model change actually helped. That turns AI from a black box you hope is working into a feature you can improve deliberately and defend to stakeholders.
We measure success in shipped value, not tickets closed. Every engagement is anchored to a few outcomes both sides can defend.
AI features that solve a real user problem, not a novelty
Answers grounded in your data, with fewer confident mistakes
Guardrails and evaluation so quality is measured, not hoped
Cost and latency kept within limits the product can afford
Everything lands in your repositories, your cloud, and your control. Nothing is locked behind us.
AI feature built into your product
Retrieval over your own data where relevant
Guardrails, prompt design, and safety handling
An evaluation harness to measure and track quality
AI integration runs on the ai & automation playbook. Boring on purpose, predictable by design.
We pin down the use case, the data available, and the cost of getting an answer wrong before building anything.
We design the retrieval, prompts, guardrails, and the human-in-the-loop points that match the risk.
We integrate the feature or automation into your product and stand up an evaluation harness alongside it.
We ship behind flags, watch quality, cost, and latency on real traffic, and tune before widening.
We monitor accuracy as the world drifts, retrain or re-prompt as needed, and keep the guardrails honest.
The everyday kit our team reaches for on this work. None of it is sacred; every choice is justified against the problem.
Have a different one? Send a single email; we usually answer within a business day.
Ship AI that earns its place in the product, not the pitch deck.
Automate the repetitive work that eats your team's week.
Assistants that answer from your data and know their limits.
Turn your data into forecasts people actually use.
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