Service 03

Generative AI and agents built with purpose

Develop grounded GenAI applications and controlled agentic workflows that support real work and can be evaluated responsibly.

How we can help

Discuss your challenge

One+i helps teams identify where language models and agents can improve a workflow, then design the surrounding system so it remains understandable and governable. That includes retrieval, prompts, tools, orchestration, evaluation, observability, and adoption.

Typical areas of work

  • LLM application and agent opportunity assessment
  • RAG, prompt, tool, and workflow design
  • Agent orchestration and human-in-the-loop patterns
  • Evaluation, observability, safety, and adoption

Topics in focus

Current themes shaping this work.

These are the practical themes we consider as technology, operating models, and expectations around AI continue to evolve.

  • Agentic workflows, tool use, and interoperability
  • RAG, hybrid retrieval, reranking, and grounded generation
  • Agent and RAG evaluation, tracing, and regression testing
  • Multimodal applications, model routing, latency, and cost

Who this is for

A useful engagement starts with the context around the decision.

Organizations exploring GenAI applications, knowledge assistants, copilots, or agentic workflows that need to move beyond a compelling demo.

What you can leave with

  • A bounded GenAI or agent use case connected to real work
  • A design for context, tools, permissions, evaluation, and human handoffs
  • A prototype or delivery plan with measurable quality and operational requirements

Related reading

Keep exploring the question.

Read more from the One+i journal, then start a conversation about the context behind your work.

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