Our Mission
To democratize compliance AI by making cutting-edge SLM technology accessible, affordable, and secure for every regulated organization.
Sovereign
Your models and your data stay in your environment - in-region, on your infrastructure, never leaving your control.
Auditable
Every output carries traceable reasoning, so decisions hold up under examination, not just internal review.
Compliance-Specific
Small language models tuned to your compliance task - accurate where it matters, governable where it counts, without the cost and opacity of frontier LLMs.
01 - The journey, told as a compounding sequence.
Our Story
Compact Machines builds sovereign compliance models for regulated finance. We did not start there - we got there by watching the same pattern repeat until it was undeniable. Every phase is a small, specific bet that turned out to be a more general one.
2024 - PHASE 0 - THE FIRST PROOF
The pattern showed up in document review.
Our first use case was M&A due diligence - teams drowning in hundreds of unstructured PDFs per deal, the same checklist every time, the same anxiety about what got missed. We built HudLink to turn that mess into structure: extract the entities, map them to a framework, and make the result analyzable and auditable. It worked - but the lesson wasn't the product. It was the shape underneath it: a repeatable way to turn unstructured regulated documents into structured, defensible data anyone could examine.
UNSTRUCTURED -> STRUCTURED - DOCUMENT REVIEW - THE PATTERN
2025 - PHASE 1 - THE PATTERN
The workflow was the IP.
The people who came to us were industry leaders who'd tried to put AI to work inside financial institutions and hit the same wall - generic models couldn't meet compliance requirements, and nothing was safe to point at sensitive workflows. They wanted an AI platform their compliance teams could actually use: for vendor risk, audit prep, exam response. The document type kept changing; the pattern never did - add an entity, clone a framework, build something that holds up, hand it to someone with subpoena power. HudLink was one expression of it. The real asset was the factory that could produce it again and again.
COMPLIANCE-FIRST - AUDIT PRIMITIVE - FACTORY THESIS
2025 - PHASE 2 - THE MOAT
Generic models can't know your firm.
Every institution wanted AI that knew their playbook, their counterparties, their risk language - and frontier API calls bled data out of the perimeter. That's the moat: a factory that compresses an institution's domain knowledge into a small, owned model, running on a single GPU, sharpening with every decision its experts make. Sovereign by construction. Not a model you rent - one you own.
SLM FACTORY - SOVEREIGN DEPLOYMENT - COMPOUNDING MEMORY
2026 - PHASE 3 - THE PROOF AT SCALE
Pointing the factory at financial crime.
AML, fraud, sanctions, KYC - the largest evidence-heavy regulated workflow in financial services. For each institution the factory builds a Compliance-Specific Model the bank owns outright. It gets sharper the more analysts use it, and every alert is defensible the day a regulator walks in. Financial crime is not the company - it is the hardest place to prove the factory works.
CSM - AML / FRAUD - EXAMINER-READY
TODAY & FORWARD - PHASE 4
One factory, many regulated workflows.
The factory pattern extends anywhere a regulated institution needs a model it can defend, a workflow it can audit, and an asset it can own - credit risk, vendor risk, model validation, exam response. HudLink was the first workflow. CSM is the first model. The market we are really in is sovereign SLM infrastructure for regulated industries.
SOVEREIGN SLM INFRA - REGULATED WORKFLOWS - MULTI-DOMAIN
Our Team
Experienced leaders in ML, infrastructure, and financial software.
Brett Nakonechny
CEO & Co-founder
Former investor and developer with 10+ years in de-risking financial data and AI/ML.
Fatima Nakonechny
COO & Co-founder
Former investor and operations specialist with 6+ years in growing financial platforms.
Zaveen Waqar
Senior AI Engineer
Built and scaled multiple proprietary financial AI architectures, models, and platforms.
Shozib Abbas
Senior Software Engineer
AI-native financial software platforms builder with 4+ years of experience in banking and fintech.