zenlabsai

We design, build and run AI agents, knowledge search and document automation inside your workflows. On your data and your infrastructure.

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Studio briefzenlabsai

01 / 02

zenlabsai is an AI engineering studio. We take AI from a promising pilot to a system your teams use every day.

02 / 02

We ship systems, not demos: built on your data, tested against your real cases, and kept running after launch.

01 / 06Solutions

Five ways we put AI to work.

We start with one process where the value is clear and the data already exists. Then we build it properly.

In production

Every system ships with monitoring

You see what runs, which version is live, and whether it still passes its tests.

Production systemsLive
  • Contract assistantKnowledge search / v3.2
    Healthy
  • Invoice intakeDocument pipeline / v1.8
    Healthy
  • Support triage agentAgent / v2.0
    Evals passed
  • Policy Q&AKnowledge search / v4.0-rc
    In review
4 systemsSample data

Architecture

Built around your stack

Your data stays where it is. The model is one part you can replace.

  1. 01Your dataDocuments, databases, business apps
  2. 02Retrieval and toolsSearch, APIs, actions with permissions
  3. 03ModelOpenAI, Anthropic or open-weight
  4. 04Guardrails and evalsChecks, test sets, human review
  5. 05Your teamsChat, email, existing tools
  1. 01

    AI agents and copilots

    Agents that work in your tools: read a ticket, check a system, draft the reply, and ask a person before they act.

  2. 02

    Knowledge search over company data

    Answers from your documents, wikis and databases, with a link to every source.

  3. 03

    Document and workflow automation

    Read invoices, contracts and forms, extract the fields, and send unclear cases to a person.

  4. 04

    Private LLM deployment

    Models in your cloud or on your own servers. We work with OpenAI, Anthropic and open-weight models.

  5. 05

    Evaluation, monitoring and governance

    Test sets, quality checks, cost tracking and audit logs, so you know how the system behaves.

Discuss your use case
02 / 06Showcases

What we build, in practice.

Three systems we often build. The screens are illustrations with sample data, not client work.

Solution showcase / 01

Enterprise knowledge assistant

Staff ask questions in plain language and get answers from your own documents. Every answer links to the page it came from.

  • Uses the access rights you already have
  • Says when it does not know
  • Works in chat, email or your intranet
Knowledge assistantAnswered

How much notice do we need to give to end a supplier contract?

Standard supplier contracts need 60 days of written notice.1Contracts signed before the 2024 policy update need 90 days.2

  • 1Supplier terms v4.pdfpage 12
  • 2Procurement policy.docxsection 3.2
2 sources citedSample data

Solution showcase / 02

Document intake pipeline

Invoices and contracts come in, the fields come out. Each field gets a confidence score, and low scores go to a person.

  • Reads scans, PDFs and email attachments
  • Sends results to your ERP or database
  • People check only the unclear cases
Document intake / invoice_0418.pdfIn review
Vendor
Sample Vendor Ltd
0.99
Invoice no.
INV-20418
0.98
Total
4,280.00 EUR
0.96
Due date
14 Nov 2026
0.62
1 field sent to review queueSample data

Solution showcase / 03

Operations agent

An agent that does a routine job from start to end, using your systems through tools. It stops and asks before it does anything that matters.

  • Every step is in the run log
  • Only uses tools you allow
  • A person approves before anything is sent
Operations agent / run 7f3aWaiting
  1. 09:02:11toolsearch_tickets(status="open", older_than="7d")12 tickets
  2. 09:02:14toolget_order(ticket.order_id)12 orders
  3. 09:02:19modeldraft_reply(ticket, order, policy)12 drafts
  4. 09:02:20approvalWaiting for a personSend 12 replies to customers?
Nothing is sent until approvedSample data
03 / 06How we work

From first call to a system in production.

Four phases. Each one ends with something you can see and use, and you decide whether to continue.
  1. Phase 01

    Discover

    We choose the use case with you and check the data behind it.

    Tangible output:A scoped plan with goals, risks and cost.

  2. Phase 02

    Prototype

    A working prototype on your own data, and a test set that defines a good answer.

    Tangible output:A prototype and an evaluation set.

  3. Phase 03

    Build

    The production system: integrations, access control, guardrails and a review flow.

    Tangible output:A system that runs in your environment.

  4. Phase 04

    Operate

    We monitor quality and cost, run the evals again, and update models when better ones arrive.

    Tangible output:Dashboards, eval reports and model updates.

04 / 06Trust

Safe to run inside a real company.

These are the rules we follow on every project. They describe how we work. They are not certifications.

  • Data stays in your environment

    We build inside your cloud or on your own servers. We do not use your data to train models.

  • Any model provider

    OpenAI, Anthropic or open-weight models. You can switch when price or quality changes.

  • Tested before launch

    Each system passes a test set built from your real cases before your teams rely on it.

  • Audit logs and access control

    Every question, tool call and answer is logged. People see only what their role allows.

  • A person decides where it matters

    Payments, customer messages and other high-impact actions wait for a person to approve them.

  • Security review

    Have a security questionnaire? Send it with your first email.

    Contact us
05 / 06From the studio

We also make our own apps.

Next to client work, we design, build and publish our own products.

Android / Coming to Google Play

Rev Music

A music player for your Jellyfin server and the music on your phone.

  • Your Jellyfin library and your phone's music in one place
  • No account with us, no ads, no analytics
  • Privacy policy
06 / 06Contact

Tell us what you want AI to do.

Send us a short email about the work you have in mind. A few lines is enough to start.

Email

Email us

What to include

  1. 01The process. What you want to change, and who does it today.
  2. 02The data. Documents, databases or apps the system would use.
  3. 03The systems. Tools it must read from or write to.
  4. 04The timeline. When you need a first result.