AI engineering consulting
Move AI from pilot to production practice.
For teams working through agents, code quality, existing systems, private data, and the habits needed to run AI in production.
Start here
AI traction sprint
For teams ready to turn AI intent into architecture, agent patterns, code quality, production habits, and training people can use in the room.
For builders at every stage.
Most AI consulting is built for Fortune 500 budgets. We work differently. AISOFT helps people pick the right tool for the right job, whether you're a CTO standing up a GenAI platform or a hackathon team trying to figure out where to start.
- Mentoring + 1:1 sessions — not just high-paid consulting
- Getting-started guidance for folks new to AI engineering
- Hands-on builds — agentic systems, RAG, fine-tuning, edge
- Production at scale when you're ready for that
The first session is free — 30 minutes, no pitch.
Getting Started
You read an article about agents or AI engineering and want to actually try something. 30 minutes with us and you'll know what to install, what to read, and what to build first. No pitch deck, no SOW.
Building Your First Thing
Past hello-world and stuck on something real. Picking a model. RAG vs fine-tuning. Sizing infra. Reviewing a hackathon submission. We've done it on commodity hardware and on enterprise clouds.
Scaling Production AI
Running multi-tenant GenAI in regulated environments. We've shipped Halo-class platforms at scale (call intelligence, document intelligence, agentic IDP) and can help you avoid the obvious traps and find the non-obvious wins.
Where we help
The practical middle of AI adoption.
When the demo is not enough and the team needs clear decisions across agents, architecture, code, data, and production.
AI value + architecture
Find where AI is useful, what to build, what to stop, and how it should fit the business.
Agentic engineering
Agents that work with humans: tool use, permissions, evals, review, escalation, and handoff.
Production engineering
AI-written code, existing systems, reliability, observability, and private-data constraints.
How we work
Steady help where AI meets the real system.
We read the architecture, code, data, and team constraints, then turn ambiguity into concrete engineering decisions.
Read
Architecture, code, agents, data, risk, and team constraints.
Shape
Clarify the agent pattern, data path, code path, and production path.
Transfer
Owner notes, guardrails, evals, and decisions your team can keep using.
Receipts
Shipped work. Not claims.
Civic data. Sports vision. Education. Creative tooling. Local infrastructure.
Undervolt
2.2M Austin permits. Energy trends. Nemotron on a 60W Jetson. First place at NVIDIA DGX AITX.
RefereAI
Ball trajectory, spin, bounce, and call explanation with vision-language models.
Studio Copilot
On-device curation, review, contracts, invoices, and feedback for creative teams.
StudyPal
Voice tutor. Schoology sync. Photo grading. Parent digests.
Ways to work together
Engagement shapes.
Traction sprint
Clarify one AI initiative and leave a practical path forward.
Agentic engineering
Work with your team on human-agent systems and production patterns.
AI architecture review
Model, data, agents, legacy constraints, governance, cost.
In-person training
One-day agentic engineering workshop for developers and teams.
Bring the real AI problem.
Send what you are trying to make work. We will reply with fit, first scope, and the cleanest next step.