AI Engineering · Applied ML · Delivery

From idea to
AI-powered business.

We design, build, and ship agentic systems that actually run your operations — not impressive demos.

Book a discovery call →See what we build
scroll · architecture↓
architecture

One orchestrator.
A team of specialised agents.

Each system we build runs on a dispatcher that routes work between specialised agents — retrieval, planning, tool-calling, critique, memory — and merges their results into a single, auditable outcome.

· dispatch· retrieve· plan· tool-call· critique· memory· merge
scroll · research↓
research

A universe of ways
to compose an agentic workflow.

For any business problem there are thousands of viable architectures — different agents, tools, routing rules, prompts, memory layouts. The right combination is rarely obvious, and what works today may not be optimal tomorrow.

So we built AutoAW to search this space for you.

internal research · v0.3in development

AutoAWauto agentic workflows

Inspired by AutoML — applied to agentic systems.

AutoAW explores the space of agentic architectures automatically: it generates candidate workflows, evaluates them against your data and goals, and returns the configuration that performs best on the metrics you care about.

search · benchmark · select · ship
Read the brief
scroll · expertise↓
expertise

Not generalists. Specialists
in applied machine learning.

Six areas of deep expertise our team brings into every engagement — the proven foundations under every solution we build.

01 · model search

AutoML

Automated model selection, hyperparameter tuning, and feature engineering — from raw data to production-ready models without manual guesswork.

02 · revenue optimisation

Dynamic Pricing

Real-time pricing that responds to demand, competition, and inventory signals — maximising revenue and margin.

03 · data unification

Entity Resolution

Link and de-duplicate records across messy, fragmented sources so CRM, analytics, and AI all see the same customer.

04 · prediction

Forecasting

Time-series and ML-based forecasts for demand, revenue, churn, and operations — built to be accurate and explainable.

05 · personalisation

Recommendation Systems

Personalised product, content, and action recommendations that drive engagement and conversion at scale.

06 · evidence

Causal Inference

Go beyond correlation — understand what actually drives outcomes so every decision is backed by evidence, not guesswork.

scroll · process↓
process

From conversation to live AI
in four steps.

A straightforward process designed for business owners — no jargon, no delays, just results.

  1. 01

    Understand

    Your business goals, the tools you use today, and where the friction actually lives.

  2. 02

    Design

    An AI plan with clear outcomes and quick wins to validate — before any big build.

  3. 03

    Build

    Built and tested against your real data and workflows, not a demo environment.

  4. 04

    Ship

    Go live with monitoring, cost controls, and ongoing iteration baked in from day one.

scroll · team↓
team

Small team. High trust.
Serious AI systems.

We work closely with business owners to understand your goals and build AI solutions that deliver real value — not just impressive demos.

Andrey Spiridonov
01 · founder

Andrey Spiridonov

Founder, Head of AI

  • Ex-Head of AI at Revinate
  • Ex-H2O.ai AutoML team
  • Founder, AutoAW.app
Pavlo Brazhko
02 · principal data scientist

Pavlo Brazhko

Principal Data Scientist

  • Co-founder, VeriHub — LLM accuracy audits
  • Ex-Terumo Blood & Cell Technologies
  • LLM evaluation & data pipeline design
Mike Turchenkov
03 · data engineering architect

Mike Turchenkov

Data Engineering ArchitectConsulting

  • Technical Architect, HCLTech — AI agent pipelines
  • Ex-Head of BigData, Jet Infosystems
  • Quantum physicist, 100+ publications
—
04 · open seat

Coming soon

to be announced

  • introductions in progress
scroll · testimonials↓
testimonials

What teams say
after we ship.

Outcomes our partners describe in their own words.

“
We replaced six months of forecasting work with a system that runs in ten minutes — and we trust the answers more than the spreadsheets.
RT
[Client name]
Head of Ops · [Retail co.]
“
Optimetrics built the orchestration layer we tried (and failed) to build ourselves for two years. The whole ops team runs on it now.
SC
[Client name]
CTO · [SaaS co.]
“
Their pricing model pays for the engagement every quarter. We're bringing them back for retention next.
MP
[Client name]
CEO · [Marketplace co.]
scroll · careers↓
careers

Join a small, high-trust team
building serious AI systems.

We’re hiring across engineering, data science, and product. Fully remote, full-time, and built around deep work.

Contact

Ready to upgrade your business with AI?

Tell us what you want to improve or automate. We’ll map out a practical AI plan and show you what’s possible in your first call.