AI expert

Useful AI, built into the heart of your products

Beyond the demos: AI agents and features that hold up in production, with controlled costs, measurable guardrails and real value for your users.

The tools of the trade

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Preview of the working environment for AI expert
davynana.dev/expertise/expert-ia

Key skills

  • LLM integration

    Streaming, tool calls, careful error and cost handling: language models integrated properly.

    Proficiency
    Proficiency : 90 / 100
  • Agents & orchestration

    Fleets of specialised agents, orchestrated server-side with realtime supervision.

    Proficiency
    Proficiency : 86 / 100
  • RAG & data

    Semantic search and vector stores wired to your business data, leak-free.

    Proficiency
    Proficiency : 82 / 100
  • Prompt design

    Instructions versioned, tested and evaluated with the same rigour as code.

    Proficiency
    Proficiency : 91 / 100
  • Evaluation & guardrails

    Evaluation sets, quality thresholds and measurable guardrails before every release.

    Proficiency
    Proficiency : 84 / 100
  • Automation

    Business workflows automated end to end, with humans firmly in charge.

    Proficiency
    Proficiency : 88 / 100

Tools & technologies

Models & APIs

  • APIs IA (LLM)

Backend & data

  • Node.js
  • Supabase
  • PostgreSQL
  • Redis

Product

  • React
  • Next.js
  • Redux Toolkit

A dedicated process

  1. Step 01

    Use-case exploration

    Identify where AI creates measurable value — and honestly rule out where it does not.

    Deliverables
    Use-case map · Cost / benefit estimate

    1 / 5

  2. Step 02

    Feasibility prototype

    A prototype wired to your real data, measured on real cases rather than cherry-picked demos.

    Deliverables
    Working prototype · Quality measurements

    2 / 5

  3. Step 03

    Product integration

    The feature integrated into your product: latency, costs and user experience refined together.

    Deliverables
    Integrated feature · Cost monitoring

    3 / 5

  4. Step 04

    Evaluation & guardrails

    An authoritative evaluation set, quality thresholds and documented guardrails before launch.

    Deliverables
    Evaluation set · Documented guardrails

    4 / 5

  5. Step 05

    Continuous iteration

    Real usage observed, regressions caught and improvements prioritised month after month.

    Deliverables
    Usage reports · Prioritised improvements

    5 / 5

Testimonial

We had launched three AI pilots before Davy: none made it past the demo. His has been running in production for eight months and our support team has won back a third of its time.
Thomas WeberChief Technology OfficerSaaS scale-up — under NDA

Let's work together

A product to build, a redesign, a team to reinforce? Let's talk about what we can create.

© 2020–2026 Davy Nana — All rights reserved

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