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Tameteq
Nebula-inspired background
AI automation & agentic systems

Your business.
Powered by AI.

We connect your company to AI systems. We design and deploy agentic solutions and AI automation that integrate with the systems you already use. These systems take over the dull, repetitive work — so your people can focus on what matters.

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Hours back, every week

We automate the repetitive steps first, so the saved time shows up in the first weeks, not after a year-long program.

Less manual glue

Agents work inside the systems you already pay for. You replace copy-paste, not your stack.

Senior oversight

No autopilot. Senior engineers design the architecture and review what agents are allowed to do.

Production, not a pilot

Access control, monitoring, evaluation, and retries are part of the build, not a later phase.

Our Philosophy

Technology is wild.
We tame it.

Agents that fit your operationWe design agentic systems around your business, your data, and the way your team already works. Every system is built to do real work, not to demo well.

Speed with engineering disciplineWe use agentic development — AI agents that help us write and test code — which lets us build systems fast. Senior engineers make sure what ships is secure, observable, and ready for the systems it touches.

Read more about our mindset
Where it grinds today

It is not hard work. It is the same work, again.

  • Someone opens sixty emails every morning and sorts them by who they belong to.
  • Someone retypes data from a PDF into your system, because those two fields were never connected.
  • Someone checks whether a reply came back, and when it did not, sends the reminder.
  • Someone assembles the same Monday report out of five different places.
  • Someone searches the documentation for an answer two other people already looked up.

A person handles each of these in a few minutes. The problem is that there are hundreds of them a month, nobody writes them down as a cost, and they are done by people you hired for something else.

This is exactly the shape of work an agent handles: a clear input, a repeated decision, and a system where the result belongs.

Where agents plug in

One run, instead of an afternoon

A process your team repeats every day, taken over by a system that reads the request, calls your tools, and reports back. We automate the repeating steps and save the time manual work would otherwise take.

Anatomy of a run

  1. 01trigger

    New request lands in the shared inbox

    0s

  2. 02plan

    Agent reads the context and picks the steps

    8s

  3. 03tool: crm

    Customer record fetched and updated

    25s

  4. 04tool: mail

    Reply drafted and queued for approval

    45s

  5. 05done

    Run logged, ready to audit or retry

    1min

Manual

1 h 20 min

Agent

1 min

Illustrative run

Inbox and ticket triage

Incoming mail and tickets sorted, summarized, and routed with a draft reply attached.

Documents to actions

Contracts, invoices, and PDFs turned into structured data and tasks in your tools.

CRM and ERP upkeep

Agents keep records current, spot missing data, and prepare the follow-ups.

Internal knowledge

Answers over your documentation, wikis, and tickets, always with the source attached.

Reporting and dashboards

A report or dashboard assembled from your systems on schedule, with charts, improvement suggestions, and predictions of where things are headed.

In-product copilots

Assistants inside your own application, backed by the server and UI we build for it.

What we build

Agents inside your systems. Repetitive work off your team.

Three ways we plug AI into a company: agents that act inside your systems, workflows that take over repetitive processes, and the integration layer that keeps both running in production.

Agentic Systems

AI agents that work inside your business — and the applications they live in. We build the whole thing: the web UI your team works in, the server behind it, and the agents communicating over it.

  • Agents with tools, APIs, and guardrails
  • Full applications: web UI and server
  • RAG over your documents and data
  • Identity, permissions, and audit trail
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AI Workflows & Automation

We take repetitive work off your team: multi-step processes orchestrated end to end — sometimes an LLM with structured output is enough, elsewhere an AI agent where fixed rules are not.

  • Workflow orchestration end to end
  • Inbox, document, and ticket triage
  • Human review before anything goes out
  • Runs you can watch, retry, and audit
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Integration & Operations

We plug agents into the systems you already run — CRM, ERP, databases, internal APIs — and keep them running once they are live.

  • CRM, ERP, and internal API connectors
  • MCP servers and tool layers
  • Data pipelines and access control
  • Monitoring, evals, and ongoing operations
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Have a process that eats your team's week? Tell us about it and we will say whether an agent is the right fix.

Message us
From practice

Two systems that already run

No marketing numbers. We describe what was built and why those parts matter.

Case 01 — agentic system over a data platform

An agent that does not just describe the platform. It operates it.

Platform users needed two things: an answer from their documentation and data, and a change made in the platform without clicking through the entire interface.

What was built

  • A RAG layer over the platform's documentation and data — answers with a link to the source, not guesses.
  • A set of tools the agent uses to actually operate the platform. It does the work instead of commenting on it.
  • An agentic system that plans the steps, calls the tools, and verifies the result.
  • Authentication and authorization: the agent acts under the user's identity and only within their permissions.
  • Monitoring: every step, every tool call, and every change can be traced back.

Why it matters

The difference between a chatbot and an agent is permissions. The moment an agent is allowed to change something, it needs an identity, limits, and an audit trail. This is the part proofs of concept skip — and the part that decides whether the system is allowed anywhere near production.

Case 02 — agentic workflow applications

The agent prepares. A person approves. The system writes it down.

Several operational processes where people did the same three steps over and over: read the input, decide, retype the result somewhere else.

What was built

  • A simple web application where the process runs and stays visible.
  • An agentic workflow that takes the input from start to finish.
  • A review screen: a person sees what the agent proposed and approves, corrects, or rejects it.
  • Those decisions collected as evaluation data, so the agent's accuracy is a number rather than an impression.
  • The approved output written back into the target system, which closes the loop.
  • Monitoring of runs, errors, and throughput.

Why it matters

Automation that never writes the result back into your system is not automation — it is one more tool to click through. And human review is not a weakness. It is how you buy trust in an agent with numbers instead of feelings.

We can put an agent where it matters: with a login, with limited permissions, with a person in the loop, and with a record of every run.

How you buy trust

We do not start at full autonomy. Often you never need to get there.

Every deployment starts with a person in the loop. How far it moves is your decision, based on measured accuracy.

  1. Level 0

    Draft

    The agent prepares the output and sends nothing. You measure how accurate it is.

  2. Level 1

    Approval

    Every output passes through a person. Their decisions are collected as evaluation data.

  3. Level 2

    Exceptions

    The agent runs on its own. A person handles edge cases and low-confidence results.

  4. Level 3

    Autonomy with audit

    The agent runs without intervention. Every run stays traceable and reversible.

Most processes are cheapest at level 2. Moving between levels is your call, and we make it on measured accuracy, not on a feeling.

DEMO

See our project in action

This demo shows how an AI agent can operate on top of an e-commerce infrastructure. The agent consumes real product data, understands the application state, monitors the user interface, and performs actions considering customer requirements and current status. The demo reflects our practical experience building AI agents in real products.

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How we start

The first step is a call. Not a project.

Free30 minutes

Show us how you work

We talk through how your team operates: what you do daily, what you do weekly, and what could not go a week without. You do not need to arrive with a specific problem — we identify it together and propose options. If you already have one, bring it and we will assess it on the spot, within thirty minutes.

Pick a time
From €220Depends on scope

Automation audit

What you get

  • A map of your processes with an estimate of the time they consume today.
  • Three automation candidates ranked by benefit against risk.
  • A technical proposal for the first workflow, including how it connects to your systems.
  • An estimate of build cost and running cost.

What we need from you

  • Two to three hours of interviews with the people who actually do the work.
  • Access to a data sample or a test environment.

The price shown is a starting point and depends on how many processes and systems fit into the audit. Every operation is different — we name the exact figure after the intro call, before anything starts. Prices exclude VAT.

If the audit shows that automation does not pay off, we will tell you. Writing “do not put AI here” is also a result — and a cheaper one than finding out in six months.

What follows the audit

  1. 01

    Pilot

    One process, a success criterion agreed up front, a person approving every output.

  2. 02

    Production

    Deployment with monitoring, access control, and documentation on your side.

  3. 03

    Rollout

    More processes on the same foundation, which makes them cheaper than the first one.

When we will tell you not to do it

  • A process that runs three times a year. The time saved will not cover the first meeting.
  • A decision where one mistake costs more than a year of savings.
  • Data that is not written down anywhere. That has to start first.
  • Something a form, a script, or one integration solves. A cheaper fix is still a fix.
BACKGROUND

About Us

At TameTeq, we believe that AI-assisted programming is a revolutionary leap in software engineering, comparable to the transition from assembly to higher-level programming languages or the introduction of object-oriented programming. These milestones fundamentally redefined how we build software, making development faster, more accessible, and more efficient. We are now at the dawn of a similar transformation.

Most of that work now happens inside companies: agents that read a request, act in the systems a team already uses, and hand the result back for approval. AI-assisted development is non-deterministic and has to be tamed and directed — that discipline is what makes those agents safe to run.

We build the systems around the agents too: the web interfaces people work in and the servers the agents run on. That is why an agentic project does not stall the moment it needs a real application behind it. To stay ahead, we study the fundamentals and read the current research.

To follow our latest articles and our progress, visit our News page.

We are a tightly-knit team driven by progress and dedicated to our paradigm. Building AI systems and robust software is our craft. We thrive on solving complex problems, maintaining order, and moving your business forward.

We care deeply because your success is our success.

Agents in production

Built to work, not to demo.

Human in the loop

Trust measured, not assumed.

Taming complexity

Mastering non-deterministic AI.

Exponential speed

From months to hours.

READ OUR ARTICLES

Latest insights from our team

Product updates, engineering notes, and practical AI/software lessons.

View all
Jun 2, 2026

AI Workflows for Internal Processes: The Fastest Path to Higher Productivity

Read article
May 20, 2026

From Chatting to Doing: What Actually Shifted in May

Read article
May 14, 2026

Ship From Your Phone: Your Own AI Delivery System

Read article
MEET US

Our Team

We are currently a small team of developers, but that means we can fully dedicate ourselves to your project. We are passionate about innovative technologies and spend time at our computers even when we don't have to, simply because we enjoy it.

Swipe to explore our team

Marian Krotil

Marian Krotil

Co-Founder & CEO

Matyáš Krotil

Matyáš Krotil

Co-Founder · Frontend & Software Lead Architect

Like our vibe?

We build agentic systems that run in production — come help us make them trustworthy.

Join our team

EXPLORE

Keep Exploring

Dive deeper into our services, learn about open positions, and review the policies that guide our work.

Services

AI Automation & Agentic Systems

Agents, AI workflows, and the integrations that connect them to your systems.

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Updates

Company News

Latest announcements and insights from our team.

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Products

DocOps AI

DocOps AI turns your internal documents into a production-ready AI knowledge base with exact source citations, role-based access, and built-in guardrails.

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News

AI Workflows for Internal Processes: The Fastest Path to Higher Productivity

Most companies today approach AI from the visible surface-a chatbot, a copilot in the inbox, or a single smart feature on the website. However, the fastest business impact often lies elsewhere: in internal processes that cost dozens of hours of manual labor every week. This is exactly where it makes sense to build small internal systems and workflows on top of your data. Systems that gather background information, sort requests, prepare outputs, monitor dependencies, and speed up tedious operations. The result isn't just saved time. It's a faster company, cleaner operations, and a team that can focus on more important work.

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