Bring product design, architecture, and full-stack engineering together. Build custom AI applications, retrieval-augmented generation, machine learning solutions, and intelligent workflows around a defined business outcome.
Product leaders and technology teams building a new AI capability or adding intelligence to an existing service.
You have a promising use case. The next challenge is to establish the right user experience, data foundation, architecture, and evaluation criteria before scaling implementation.
Define the users, decisions, workflow, and intended business benefit. Identify data sources, integration dependencies, and the behaviors that will establish acceptance.
Select an approach suited to the task: a custom LLM application, retrieval over your documents, an ML model, or an agentic workflow. Design permission boundaries and human review into the experience.
Implement the user interface, application services, data connections, and AI workflow as a coherent product. Work in reviewable increments that stakeholders can exercise.
Check representative behavior and failure cases against agreed criteria. Plan deployment, operational ownership, monitoring, and transition support alongside the build.
We agree the scope and outputs around your starting point. A typical engagement can include:
A team needs help finding information in an internal knowledge base. We map document access, build retrieval and an answer experience, and evaluate whether the result uses appropriate source material and handles unanswered questions sensibly.
Bring a priority workflow and the people who own it. We will review the intended outcome, dependencies, and constraints, then define an initial scope and acceptance criteria.
Model choice and delivery scope follow feasibility work and the needs of the product.
Plan this engagementApply Safe AI practices across the development lifecycle: specification, implementation, review, testing, and release preparation. Combine automation with clear acceptance criteria and accountable decisions.
Explore this serviceModernize legacy applications, connect enterprise systems, and develop cloud and data foundations that support your AI priorities. Sequence the work around business continuity and a practical migration path.
Explore this serviceCombine application maintenance, performance support, and AI evaluation with a clear operating model. Give the product a path to reliable operation, ongoing improvement, and team ownership.
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