Work

Platforms we’ve built, and the contracts they helped win.

Where work was delivered through a client’s own customers, we say exactly what our role was. Confidential clients stay confidential.

Case studies

Selected work

Monitors showing video frames and images with labeling bounding boxes in a dark workspace

AI data platforms

The AI data platform behind MLtwist

We designed and built the platform MLtwist runs its AI data business on — projects, people, labeling and Kubernetes pipelines.

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Empty airport security checkpoint with a baggage CT scanner and conveyor at night

$590K

TSA contract

Government · aviation security

Multimodal AI data for the U.S. TSA

Video, audio, text, images and 3D DICOS scans — processed and labeled for threat-detection models, on the platform we built.

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$Light beam refracting through a crystal sample on an optical bench in a materials lab$

$198K

DOE SBIR award

Government · materials science

PRIMED: fast materials-data search for U.S. Department of Energy researchers

PRIMED, a search and indexing platform that lets scientists share materials data and find materials by recorded and projected properties — in seconds.

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Rows of vehicles on a car dealership lot at dusk

Confidential client

Automotive · dealer telematics

Dealer telematics and lot management, rebuilt from scratch

A new telematics platform for car dealerships — built from zero, on lower-cost hardware, field tested and in production.

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A compact cluster of small servers on a steel shelf in a dark on-premises server room

< 2 weeks

Platform overhaul

Confidential client

Connected-device software

An AI-first platform rebuild behind a company’s pivot

One platform for a new embedded Linux product, running on a laptop, in AWS and air-gapped on-prem. Built so the client’s own team could finish the overhaul with AI in under two weeks.

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A freshly poured, empty concrete foundation slab with conduit stubbed up, on open West Texas ground at dusk

Your platform could be the next one here.

Most engagements start with a scoping call and a written plan.

Book a scoping call

Axio engineered the platform MLtwist runs on — how we manage projects and people, run labeling, and launch custom pipelines on Kubernetes. It’s the foundation we delivered our TSA and Department of Energy work on. They build like owners, and they ship.

David Smith

Founder & CEO, MLtwist

Engagement patterns

The shapes our projects usually take

Typical starting points and end states, not individual case studies. If one looks like your situation, that’s a good first call.

P/01

New division → in market

FROM: A new product line with a launch date and no engineering team of its own.
TO: Product site, portals, billing, integrations and cloud infrastructure — built, launched and handed off.

P/02

Stalled pilot → fielded product

FROM: Hardware works, SIMs are active, the project has stalled on software.
TO: Firmware command handling, cloud pipeline, OTA and a fleet console — shipped as a fixed-scope build.

P/03

Scripts & spreadsheets → data platform

FROM: AI data work held together by one-off scripts, email and manual QC.
TO: Project, workforce and labeling management with Kubernetes pipelines per project.

P/04

Hand-built cloud → infrastructure as code

FROM: Console-built environments on AWS, GCP or Azure that nobody can reproduce.
TO: Terraform/OpenTofu foundations, CI/CD and ongoing IaC support.

P/05

Wi-Fi-only device → dispatchable

FROM: An energy device that depends on customer Wi-Fi and can’t join utility programs.
TO: A cellular command path, a utility/aggregator interface and M&V telemetry.

P/06

Aging platform → fast and affordable

FROM: A platform that got slow and expensive as it grew.
TO: Profiling, targeted fixes, cost reduction and incremental rewrites — no feature freeze.

Talk through your project