AdaptAI Solutions · AI consulting & engineering studio

AI advice is everywhere.
Working systems are rare.

Strategy, engineering, and rollout from one studio. I map where AI pays off in your business, build the agents and automations that capture it, and stay until your team runs them without me.

Founded and run by David Nierenburg.

Model-agnostic

01 · The point

Most AI projects die in the gap between “good idea” and “someone owns this every Thursday at 09:00.”

The work starts with a real process: support triage, phone intake, invoice handling, reporting, internal search, proposal drafting. Then comes the system that removes steps, routes exceptions, and gets owned by the team that runs it.

I sit with leadership to decide where AI fits the roadmap. I also write the MCP server, tune the assistant, and wire the workflow. The value is in closing the gap between the two.

02 · Services

One studio, three jobs.

Plain language for decision-makers, real depth for technical teams.

01

Advise

Decide what’s worth building.

  • AI opportunity map & roadmap

    Where AI creates leverage in your business, what to build first, and what to skip.

  • Build, buy, or skip

    Model, stack, and integration decisions matched to your data constraints and budget.

  • EU AI Act & governance

    Risk classification, usage policy, and a documentation trail that keeps legal review short.

  • Workshops & talks

    Sessions for leadership days and teams, demonstrated on live systems rather than slides.

02

Build

Ship the system, not the slideware.

  • Agents & workflow automation

    Multi-step agents that plan, execute, and report: intake, routing, drafting, approvals, logging.

  • Voice & phone agents

    Receptionists, intake lines, and follow-up calls that answer instantly and hand off cleanly.

  • Documents & back office

    Invoices, contracts, and inbox attachments read, validated, and filed without retyping.

  • Knowledge assistants

    Private question-answering over company documents, with citations back to the source.

  • MCP servers & integrations

    Controlled assistant access to internal tools and APIs, permission-aware and auditable.

  • Custom apps

    Purpose-built software for the workflows where off-the-shelf tools end.

03

Run

Make it boring by month six.

  • Evals & guardrails

    Test suites, tracing, and monitoring that keep behavior reliable long after launch.

  • Training & handover

    Your team learns to run, adjust, and extend the system. No black box, no dependency.

  • Documentation & runbooks

    Prompts, tool definitions, deployment notes, and the Thursday-morning checklist.

  • Iteration retainer

    A standing lane for improvements once the system is part of the routine.

If the work happens on a screen and follows rules someone can explain, it’s a candidate. The uncommon shapes are often the best projects. Describe yours and I’ll tell you if it’s buildable.

03 · Use cases

Concrete starting points.

Representative blueprints, not claimed results: the systems that ship first and prove value fastest.

Ops

Inbox-to-action workflow

Incoming requests are classified, enriched with account context, drafted into the right response, routed for approval, and logged back into the team’s system.

  • Fewer handoffs
  • Consistent first drafts
  • Clear exception queue

Voice

Phone intake that never queues

Calls answered instantly: the agent qualifies the request, books or routes it, and posts a summary where the team already works.

  • Answers around the clock
  • Clean handoffs to humans
  • Every call logged and searchable

Knowledge

Company knowledge assistant

Wikis, drives, and tickets are ingested into a private index. The team asks in plain language and gets answers with citations back to the source.

  • Answers with sources
  • Permission-aware retrieval
  • Stays inside company boundaries

Back office

Invoice-to-ledger pipeline

Invoices arrive by email, are read and validated against orders, and post to accounting. Exceptions land in one short review queue.

  • No manual retyping
  • Validation before posting
  • Review exceptions, not everything

Integration

Internal tool bridge

A custom MCP server lets approved assistants search company docs, read project state, create tickets, and run safe internal actions from one controlled interface.

  • Permission-aware tools
  • Auditable assistant actions
  • Reusable across teams

Research

Autonomous research agent

An agent takes a research brief, works through the sources, drafts the deliverable, and files the result with citations and open questions for review.

  • Cited source list
  • Draft ready for review
  • Open questions surfaced

04 · Process

Audit. Prototype. Ship. Embed.

  1. 01

    Audit the workflow

    Map the process, tools, permissions, data sources, and failure points. Pick the first useful build.

  2. 02

    Prototype with real inputs

    Build a narrow version quickly so the team can judge behavior against actual work.

  3. 03

    Ship the reliable version

    Add tests, guardrails, documentation, monitoring, and clean handoff paths.

  4. 04

    Embed the habit

    Train the users, refine the workflow, and leave the team with ownership instead of dependency.

05 · Founder

Who you’re working with.

AdaptAI is run by one senior person across the whole engagement. The person who talks strategy with your leadership is the same one who writes the MCP server, tunes the assistant, and sits with your team on rollout day.

That changes what gets built. No handoff between a strategy deck and a delivery bench, no translation loss, no junior rotation. A direct working relationship with the person accountable for the result.

David NierenburgFounder, AdaptAI Solutions

06 · Questions

Before the first call.

Do we need a clear AI roadmap before talking?

No. The first useful step is usually a workflow audit. If the best answer is “don’t build yet,” I’ll say so.

Who owns the code and setup?

You own the code, prompts, tool definitions, deployment notes, and runbooks. I build so your team can run the system without a black box.

Can you work with sensitive internal tools?

Yes, with the right boundaries. MCP servers, assistant tools, and automations should respect authentication, permissions, audit needs, and data handling rules from the start.

Do you handle EU AI Act and data-protection concerns?

Yes. Risk classification, data boundaries, and the documentation trail are part of the build, not an afterthought. Most workflow systems land in the lower risk tiers, and knowing that early keeps legal review simple.

Is this technical consulting or business consulting?

Both, in sequence. The business case decides what should be built. The technical work proves whether it can be made reliable.

What does an engagement cost?

The 20-minute audit is free. After that: a fixed-price prototype, then a scoped build. You always know the number before work starts.

07 · Start

Describe the workflow that’s slow. I’ll reply with the clearest next step.

A useful first message is specific: which process, which tools, what the team already tried. I reply within one business day.