AIADAPT

AI adoption studio · David Nierenburg

AIADAPT

I design and build AI systems for real workflows: agents, automations, MCP servers, and the rollout that makes them stick.

Book a 20-minute audit

AIAdapt Solutions. AI systems for company workflows. Founded by David Nierenburg.

01 · The point

AI adoption fails when it stops at advice.

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

I can sit with leadership and decide where AI fits the roadmap. I can also write the MCP server, tune the assistant, and wire the workflow. Most AI projects die in the gap between "good idea" and "someone owns this every Thursday at 09:00". The job is closing that gap.

02 · Services

What I build.

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

  • AI consulting & strategic overview

    A clear map of where AI creates leverage in your business, what to build first, and what to skip.

  • AI governance & EU AI Act readiness

    Risk classification, usage policy, and the documentation that keeps compliance straightforward.

  • Speaking & workshops

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

  • AI agent systems

    Multi-step agents that plan, execute, and report: research, operations, browser work, scheduled jobs.

  • Automated workflow setup

    Intake, routing, drafting, approvals, and logging, automated end to end with human review on exceptions.

  • 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 manual retyping.

  • RAG & knowledge assistants

    Private question-answering over company documents, with citations.

  • Data & BI assistants

    Plain-language answers from your business data, with reports generated automatically on schedule.

  • Custom MCP servers

    Controlled assistant access to internal tools and APIs.

  • Plugins & skills

    Installable capabilities that make an assistant behave like part of your team's workflow.

  • Custom apps & programs

    Purpose-built applications shaped to the workflow rather than the other way around.

  • LLM evals & reliability

    Test suites, tracing, and guardrails that keep the system reliable in month six.

  • Model & stack selection

    The right model, hosting, and integration path for your data constraints and budget.

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

03 · Use cases

Concrete starting points.

Representative blueprints rather than claimed results: the kinds of 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
RAG

Company knowledge assistant

Wikis, drives, and tickets are ingested into a private index. The team asks questions 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
MCP

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 clients
Agents

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 notes, 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 · Contact

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.

david@aiadapt.se GitHub

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.