Generative AI solutions
Most AI pilots stall between a good demo and a system people rely on. We close that gap: agents that use your tools under clear permissions, retrieval that cites its sources, and evaluation sets that tell you when a change made things worse.
Build workflows in which agents plan tasks, use approved tools, and pass work between specialist capabilities. Define checkpoints, human approvals, and recovery paths before connecting agents to business processes.
Workflow design · Tool integration · Human review
Retrieval-augmented generation (RAG) brings relevant information from your documents and systems into an AI answer. We work through ingestion, retrieval, context selection, and source citations so people can inspect the information behind a response.
Document ingestion · Retrieval · Source citations
Shape agents around a specific job: research, document processing, knowledge assistance, or workflow coordination. Define the inputs, tools, permissions, and completion criteria for each capability.
Research · Documents · Knowledge · Operations
Bring an assistant into an existing product or connect an agent to an API. Design the user experience, session context, tool contracts, and handoff to a person alongside the model interaction.
Embedded assistants · APIs · Tool calling
Build a representative evaluation set and test task completion, groundedness, retrieval relevance, and failure cases. Compare changes in quality, latency, and usage before a new configuration is released.
Evaluation datasets · Regression checks · Failure analysis
Make data access and tool permissions explicit. Define logging, review points, and fallback behavior so the team operating the system can understand what happened and intervene when needed.
Access boundaries · Traceability · Fallbacks