Agent Reliability LabRequest a scope
Estonia · asynchronous studio

Your AI agents work in the demo. Production is where they break.

Failures in production almost never start in the model. They start in the missing management layer: unclear tasks, no safety gates, no monitoring, no owner when something goes wrong. We build agents, automation and websites, then put that layer on top. Work starts from a written brief, asynchronously. No call required.

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2006
Operating since
150+
Delivered projects
10+
Agents in daily production

These figures are for the studio as a whole, including work shipped before the Agent Reliability Lab name. See cases.

Services

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Automation

AI agents and automation

Assistants for inquiries, documents and scheduling, plus research agents that watch prices, risk and signals. Human-approval gates. Pilot in 1–2 weeks.

Learn more →Flagship

AI agent audit

Audit and stabilise agents already in production: Harness Health Check, risk map, management layer, then a sprint or a fractional advisory if you want us to stay.

Learn more →Consultants

AI consultant and chatbots

A grounded consultant on your site that will not invent products, plus Telegram and WhatsApp bots that capture a lead and hand a brief to a human.

Learn more →Websites

Websites

Corporate sites and B2B catalogues with a request form instead of a cart, CRM and ERP integrations, SEO-ready. Four weeks from layout to launch when the brief is ready.

Learn more →Apps

Web apps

PWA and Telegram Mini Apps: storefront or booking in the messenger, a home-screen icon, Stripe and cards, optional Telegram Stars, push. One codebase, two channels.

Learn more →SEO

SEO and growth

SEO for Google in named regions and narrow niches, Google Ads, interface reliability audits on GA4 or Plausible, a monthly written report. Usability as slice, funnel or fixes — formats, not a price table.

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Materials

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VerificationWhy AI agents game their own tests, and how to isolate verificationAn agent that writes the test will pass it. Isolate the falsifier, allow BLOCKED, and stop treating a green self-report as a release signal.Read →AutomationA macro dashboard built by a multi-agent ensemble on DuckDBBeat rate is a first derivative. A DuckDB panel plus a three-family ensemble reads acceleration — with a falsifier on every scenario.Read →AutomationMulti-dimensional portfolio stress-testing against liquidity shocksVaR is calm-weather maths. A 12-by-6 shock matrix and a 60 percent margin ceiling show where a book dies in a liquidity event.Read →
Free · open · no sign-up

Courses

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8 modules · free · open

Harness Engineering: why agents fail — the harness, not the model

Model capability is not execution reliability. When a long task dies mid-run, the bottleneck is almost always the environment around the model.

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8 modules · free · open

Management Methods for AI Agents: OODA, GTD, PDCA, TOC, First Principles, OKR

An agent on a real task is already doing management work: goals, context, decisions, tools, review. Unstable runs are usually a broken loop, not a weak model.

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9 modules · free · open

Grounded AI Consultant: how to stop a store assistant from inventing products

A catalog bot that invents a SKU or a price is not a cute model glitch. Grounding is a constraint: retrieval, a runtime guard, and a human handoff.

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Reliability

How we work

  1. 01

    Written brief

    what the system does, where it fails, what you need back.

  2. 02

    Scoped proposal

    what we will inspect or build, and what we will not.

  3. 03

    Pilot in 1–2 weeks

    a working slice, not a slide deck.

  4. 04

    Handover with a runbook

    who watches it, who stops it, what happens next.

Agent Reliability Lab
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