AxionX Digital
For Startups

Ship AI fast.
Do it right.

AxionX gives startups the AI engineering muscle of a large team at startup speed and cost. From your first fine-tune to a production pipeline, we move at the pace your roadmap demands.

Ship in days, not months
💰Startup-friendly pricing
🎯Senior engineers only
Typical startup timeline
Day 1
Discovery call + scoping
Day 2–3
SOW signed, engineers assigned
Week 1
Dev environment + pipeline running
Week 2–3
First fine-tuned model checkpoint
Week 4
Eval framework live + model shipped
Typical time to first model~4 weeks
What we build

The AI stack your startup needs

Purpose-built for resource-constrained teams. No enterprise bloat, just the capabilities that move the needle at your stage.

🚀

Fast ML Pipeline Setup

Get from idea to reproducible training pipeline in days. We set up your Docker environments, dataset versioning, experiment tracking, and CI/CD so your team can iterate without friction.

DockerDVCW&BCI/CD
🧬

Fine-Tuning on a Budget

SFT and DPO fine-tuning of open-source models (Llama, Mistral, Phi) using parameter-efficient methods like LoRA, delivering production-ready models without the compute bill of training from scratch.

LoRA / QLoRAOpen-Source ModelsCost-Efficient
🤝

Fractional AI Engineering

Senior AI engineers available part-time or sprint-based, perfect for startups who need expert bandwidth without a full-time hire. We plug into your workflow and deliver like a member of your team.

Part-TimeSprint-BasedAny Stack
📊

Starter Dataset Packages

Curated, annotated datasets for instruction tuning and evaluation, designed to get your first fine-tuned model trained on high-quality data without building an annotation operation from scratch.

SFT DatasetsEval SetsFast Delivery
🔬

Lightweight Evaluation

Simple but rigorous eval frameworks that give you confidence in your model before shipping. Custom rubrics, automated scoring, and clear pass/fail criteria without enterprise overhead.

Rubric DesignAutomated ScoringQuick Setup
🛠️

Dev Tooling & Automation

GitHub Actions for your ML pipeline, model versioning, and deployment scripts that let your engineering team ship AI features without getting stuck in ops work.

GitHub ActionsModel VersioningDeploy Scripts
By stage

We grow with you at every stage

🌱
Pre-seed / Seed
Validate your AI thesis fast
  • Proof-of-concept fine-tuning
  • Lightweight eval to guide iteration
  • Fractional engineering bandwidth
📈
Series A
Build production-grade AI infrastructure
  • Reproducible training pipelines
  • Expert dataset curation for your domain
  • Engineering pod for scale-up
🏗️
Series B+
Operate at scale with confidence
  • CI/CD-integrated evaluation
  • Full model registry and monitoring
  • Embedded team for ongoing delivery
Why startups choose us

Senior expertise.
No junior padding.

  • Every engineer has shipped production ML, with no onboarding ramp
  • LoRA / QLoRA fine-tuning on open-source models keeps compute costs low
  • Async-first communication that fits your engineering culture
  • Flat, transparent pricing, with no surprise scope creep invoices
  • You own all code, models, and data, with no lock-in, ever
  • Free 30-min discovery call to scope your first project

"Their remote engineering pod integrated within days. With overlapping hours and a culture of mentorship, they delivered features on time while raising the bar for our whole team."

B
Head of Engineering
B2B Tech Startup

Flexible engagement models

Quick Sprint
Defined scope, fixed timeline
1–4 weeks
Part-time Pod
Ongoing fractional engineers
Monthly
Project-based
Full project ownership
4–12 weeks
Get started

Ready to ship your first model?

Free 30-min discovery call. We'll scope your first project and get engineers assigned within 48 hours.