Five focused areas, led by RAG and LLM work. If a brief falls outside them, we will say so early.
Retrieval systems that answer from a defined knowledge base, with source tracking and a path to iterate on quality.
Useful when Consultants, support teams, or internal staff spend too long searching documents that already exist.
Add language-model features to an existing product: copilots, document tools, content workflows, and API-backed assistants.
Useful when A partner has a client who wants AI inside a current product, but the in-house team should not pause other delivery to learn the stack.
Tool-using agents and automations that complete multi-step work, with human review on the steps that need it.
Useful when Repetitive operations, research, or hand-offs are eating delivery time that should stay with the partner’s client work.
Application, API, and integration work so AI features sit cleanly inside the product instead of as a disconnected demo.
Useful when The AI piece is only useful if it talks to the existing CRM, database, auth, or client portal — and that engineering still has to ship.
Forecasting, scoring, and classification models connected to the data and workflows a team already uses.
Useful when A project needs predictions or ranking, not only a chatbot, and the current team lacks ML delivery capacity.
When it is part of one of the engagements above, we can also support the data preparation, dashboards, web interface, and automation around the AI piece. These are not offered as standalone services. If your brief is outside the five areas above, we will say so early.
Share a short brief. We’ll tell you whether the work is a fit and how a collaboration could be scoped.