Applied AI Engineering

A senior AI team that transforms your vision into a real, working AI solution.

Start a conversation See what we do

20+Years in enterprise IT

2–3 wkFrom brief to working prototype

~1.5 moPrototype to production

100%Deployed in your environment

Senior professionals AI-native delivery Real deployments

Bowman-Architect is an enterprise AI engineering and consulting practice. We combine two decades of solution architecture, cloud, and business-requirements work with a delivery model rebuilt around modern AI tooling.

That combination lets us move at a speed traditional teams cannot match — while keeping the engineering discipline that production systems demand. We design from a defined business requirement, build top-down, and you watch the platform grow while requirements are still being refined.

We work alongside your people and partner cleanly with other vendors and delivery teams. No lock-in, no theatre — just clear statements of skill, scope, and outcome.

What we are good at

Deep, hands-on capability across the modern AI stack — from agentic systems and deep research to private, on-premise models.

Agentic systems & deep research

Multi-step research agents with logged reasoning, parallel research threads, and best-result selection over massive unstructured datasets.

Explainable AI

Full response telemetry — the thought process, tools used, hypotheses, and the exact data behind every number, so users can trust the answer.

Chat with your data

Plan-driven analysis over large, unstructured datasets that non-technical decision-makers can interrogate and steer in plain language.

Private & custom models

Local model deployment, fine-tuning, and custom training sets for data you cannot send to managed platforms — or volumes where cost matters.

Rapid MVPs & prototypes

Validated, deployed MVPs in weeks — proving real business scenarios in a live environment, not on paper.

Executive AI advisory

Continuous, board-level guidance that turns market-proven methods into actionable programs, plans, and delivery leadership.

Joint product development

We co-build new products with your team — pairing deep AI expertise with product-minded, experience-led UX design to take ideas from vision to shipped.

Selected use cases

A sample of problems we have framed and solved across healthcare, automotive, customer experience, marketing, and the public sector.

Voice-of-the-customer deep research

US / Healthcare

Problem: Analysing 1M+ reviews where context limits and content loss break naive summarisation and RAG. Only sentiment and cohort grouping were possible; real key-driver analysis was out of reach on a massive, unstructured dataset.
Solution: A deep-research agent with fully logged steps and reasoning, running parallel research threads and selecting the strongest result to control evaluation variance.
Result: A research paper / thesis you can converse with — including the steps the agent took — turning an unanalysable dataset into defensible insight.

Stack: Azure, Databricks, custom solution

Explainability for agentic analysis

US / Automotive

Problem: Non-data-scientist users running agentic analysis could not see how an answer was produced or which data was used — and explainability must not become a second AI step that merely justifies the first.
Solution: Full response-generation telemetry: the thought process, tools used, hypotheses formed, conclusions, numbers found, their locations, and how they were used.
Result: A clearer, traceable answer mechanism that surfaces logical errors and shows exactly which sources and logic drove each calculation.

Stack: Azure, Databricks, custom solution

Chat with a dashboard

US / Customer Experience

Problem: Business experts who cannot write Python still need to ask complex questions of large, unstructured datasets that traditional tools (Excel, warehouses) cannot handle.
Solution: A "chat with data" mechanism that plans against the dataset, generates a traceable analysis, and lets users converse with the reasoning and steps.
Result: Far more accurate, detailed answers than map-reduce summarisation — at higher token and runtime cost, but with incomparably better precision.

Stack: AWS, vllm, custom agents

B2B lead management

US / Marketing Technology

Problem: People dislike filling forms. Qualified lead capture (name, email, title, company) was leaking because the form-based flow could not hold attention.
Solution: Natural-language chat replacing forms — AI-driven conversation, data normalisation, classification, and direct integration into Salesforce.
Result: More qualified leads and longer interactions, with company enrichment from the email domain and automated internet research to qualify the account.

Stack: Azure, OpenAI, custom solution

Vibe Work — agentic task management

Enterprise / Government

Problem: AI capability needs to live inside existing workspaces (Teams, Outlook, Google Docs/Sheets) to keep context and automate transactional back-end processes.
Solution: A vendor-independent platform where users trigger role-specific AI agents via tags, with a harness for virtualised, file-based workflows.
Result: Seamless AI inside existing workflows that keeps full context and acts as a loose integration layer for complex back-end automation.

Stack: Digital Ocean, Anthropic, custom solution

Track record

A pragmatic overview of what the team has delivered. It reflects our delivery capability across sectors and geographies rather than a marketing showcase.

Our engagements are covered by non-disclosure agreements, so we never name clients. Each reference describes the delivery scope and outcome by industry and region instead.

Cross-industry · Leadership

Enterprise AI adoption workshops

Workshops for non-technical audiences that catalyse AI adoption and surface new, viable use cases the business can act on.

Engineering teams

Developer team AI enablement

Hands-on workshops that upskill developer teams on how to build with — and work effectively alongside — modern AI tooling.

US · Healthcare

Deep research over 1M+ records

Turned an unanalysable review corpus into defensible, conversational research where naive summarisation and RAG had failed.

US · Automotive

Explainable agentic analysis

Gave non-technical users a fully traceable view of how each answer was produced and which data and logic drove it.

US · Customer Experience

Chat with enterprise data

Enabled business users to interrogate large, unstructured datasets in plain language with traceable, plan-driven analysis.

US · Marketing Technology

Conversational B2B lead capture

Replaced forms with AI-driven chat integrated to CRM, lifting qualified-lead volume and enrichment-based profiling.

Enterprise · Government

In-workspace agentic task management

Embedded role-specific AI agents into existing tools (Teams, Outlook, Docs) to automate back-end work while keeping full context.

Enterprise · Government

Rapid MVP & proof-of-concept delivery

Delivered validated, deployed MVPs in weeks — proving real business scenarios in a live environment rather than on paper.

Why "Bowman"

The name is a deliberate metaphor.

On a racing yacht, the bowman works at the front of the boat — the first to spot what is coming, calling the trim and the gybe while the crew drives speed. It is a position of skill, nerve, and precise timing.

That is how we like to work with our clients: out front on the technology, reading the conditions early, and making the small, decisive calls that keep the whole team fast and on course.

Founded in Budapest in 2020 by Laszlo Boa, the practice grew out of two decades of enterprise architecture — and a conviction that AI has changed the DNA of how software gets built.

The stack we build on

Portable by design — built on industry-standard, open-source inference and containerisation so your solution is never trapped on one vendor.

Models

OpenAI

Anthropic

Google

Meta / Llama

Open-source LLMs

Local & private models

Cloud & platform

Microsoft Azure

Amazon Web Services

IBM Cloud

Red Hat OpenShift AI

Open-source inference

Containerisation

Application

Next.js

React

Node.js

Python

How we work

A top-down, rapid delivery loop powered by senior people and superior AI tooling.

Frame the business case

We start from a defined business requirement — understanding the environment, clarifying the case, and developing concrete use cases.

Design top-down

Solution architects shape the platform end-to-end before committing to detail, so the system stays coherent as it grows.

Build organically

You see your platform building and growing while requirements are still being refined — real software in a live environment.

Deploy & hand over

A working IT solution deployed in your environment, ready to take to production, scale, or transform — your call.

How we engage

Remote-first and ready to plug into your teams — on site when it matters.

Remote-first

We work primarily remotely, with the tooling and discipline to deliver production systems without being in the room.

On site on request

Based in Budapest, the team travels and works on site whenever a project genuinely needs it.

Partner-friendly

We collaborate cleanly with other vendors, services teams, and in-house engineering — no lock-in, no territory games.

Ready to move at AI speed?

Tell us the problem. We will tell you, plainly, what is possible and how fast we can prove it.

Get in touch