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For company leaders

Our founders built and sold an AI company used by 150+ organizations. Now we help you build teams of people and AI agents.

Start with one workflow: who does what, what gets checked, and who signs off.
Your people keep the decisions; AI agents do agreed parts of the work.

Connected human–AI teams

The team you would work with.

One team covers the technology, the management, and the people side of each workflow.

Our research so far: 11 research papers, one already published as a peer-reviewed journal article, and 5 patents pending. This November we present at IEEE ICDM 2026.

Meet the full team

  • Dmitriy Istomin

    Co-founder, CEO · Product and operations

    Founded Examus, an AI company acquired by Constructor Tech in 2022. Runs 8Hats Lab day to day with AI agents.

  • Taras Pustovoy

    Co-founder · Trust framework and AI agent methodology

    Built CourseFactory, acquired by Smartcat. 25+ years building software, most recently AI products.

  • Alexander Volkov, PhD

    Co-founder, Research Lead · Research design and evaluation

    Engineer. Leads our research and how we evaluate the work of AI agents.

  • Mariam Mamedli, PhD

    Co-founder · AI in production, data and product

    Economist. Fourteen years in banking and fintech data; led the global quant product line at CEIC, an economic data provider.

Where to start

Choose your next decision.

  • Founders and CEOs

    Evaluate AI work on your own material before deciding what to fund next.

    Evaluate your next AI decision

  • HR and People executives

    Support people through AI transformation by shaping AI agents around human judgment, wellbeing, and accountability.

    Map people and AI work

The management challenge

More output. Three management gaps.

A draft arrives ready to use. Before the team relies on it, three questions still need answers.

Quality

Can we verify it?

A polished document can still be unsupported, internally inconsistent, or impossible for the next reviewer to verify.

Coordination

Is the context the same?

People combine outputs without sharing the assumptions, sources, or instructions their AI agents worked from.

Accountability

Who can approve it?

AI agents can prepare and compare. A named person still needs the context and authority to approve and release the work.

A different way to work

From human in the loop to human on the loop.

Start where a person checks every step. Move, one workflow at a time, to where a person sets the standard and rules on the exceptions. The record shows when a move is due.

Human in the loop

01Human in the loop

A person checks every step.

Every AI output waits for a person before it moves. Slow, and the right place to start: this is where the review standard gets written down.

The person sits inside the loop. Nothing moves until they have read it.

Human in the loopThe person sits inside the loop. Nothing moves until they have read it.Drafts fromsourcesRevisesthe draftChecks every stepand decides

What moves a workflow to the next stage

The record, not the calendar: accepted output steady at the agreed standard, correction effort falling, and no unresolved exception older than the review window.

Judge the whole result

Compare accepted output, review time, and correction effort against the same standard. Count setup and coordination too.

From the idea to the work

See what changes in the work.

Choose a workflow to start.

Sales enablement

Knowledge → action
  1. The problem

    Reps work from different versions of the truth. Leads go quiet and CRM records fall behind.

  2. The workflow change

    Connect AI agents for sales to verified company knowledge, calls, and CRM—with every answer tied to its source.

  3. The working result

    One current sales line. Quiet leads surface. People keep the buyer relationship.

Who does what once it runs
  1. A person: Rep asks
  2. An AI agent: Answer, source attached
  3. An AI agent: Quiet lead surfaced
  4. A named person decides: Rep decides the reply
Explore all use cases

Your next step

Continue with your decision.

  • Founders and CEOs

    Evaluate AI work on your own material before deciding what to fund next.

    Evaluate your next AI decision

  • HR and People executives

    Support people through AI transformation by shaping AI agents around human judgment, wellbeing, and accountability.

    Map people and AI work

How we work with you

Start with one workflow. Decide after the result.

Choose a bounded project with a clear operational result. Agree what success means, run it on your material, then decide what deserves the next investment.

  1. 01

    Find the review gap

    What you get.

    A map of who does what, what gets checked, and where the work stalls.

    Explore our research
  2. 02

    Design the shared work

    What you get.

    A workflow design, agreed success measures, and a cost projection.

    Explore workflow consulting
  3. 03

    Run it on your material

    What you get.

    A running workflow, measured results, and a clear next move.

    Explore our products
Our products, where they fit:Organization ModelAgents Coworking (opens in a new tab)The Agents University (opens in a new tab)

Start with one workflow. Agree the acceptance standard. Compare production, review, and correction effort before deciding what to expand.

Choose your next decision.

  • Founders and CEOs

    Evaluate AI work on your own material before deciding what to fund next.

    Evaluate your next AI decision

  • HR and People executives

    Support people through AI transformation by shaping AI agents around human judgment, wellbeing, and accountability.

    Map people and AI work

Bring one workflow. Find the next step.

Bring one workflow where context, review, or ownership gets lost. Identify whether there is a bounded first project to discuss.

Bring us one workflow