About
An AI engineering and consulting partner
PhiGrad AI exists for one reason: most AI projects stall between a working demo and a system a business can depend on. We close that gap: architecture, evaluation, security, optimization and deployment.
We are a small senior team. The people who scope your project are the people who write the code, run the evaluations and sit in the security review.
We are deliberately not a generic software shop, a chatbot agency or an AI training provider. Our work is engineering: agents, document intelligence, model adaptation, inference performance and AI security.
Name
Why PhiGrad?
PhiGrad brings together two ideas that are central to AI: Phi, representing intelligence, balance and optimization, and Grad, inspired by gradients through which machine learning systems learn and improve.
PhiGrad represents our belief that AI should not just work, but continuously improve.
Founder
Led by an engineer, not an account manager
Engagements are led hands-on by our founder, who works directly with your CTO or engineering lead through architecture, build and production readiness. Background spans applied machine learning, LLM and small-model engineering, high-throughput inference and AI security.
Focus
Agents & document intelligence
Depth
LLM/SLM adaptation & inference performance
Standard
Evaluated, secured, cost-measured
Detailed background, references and prior engagement summaries are shared on request.
How we work
Working principles
Evaluation before scale
Nothing ships without a task-level test set. Improvements are proven against it, not argued about.
Smallest model that clears the bar
We start from the quality target and work down to the cheapest, fastest model that meets it.
Failure modes are designed
Retries, fallbacks, confidence thresholds and human review are part of the architecture.
Security is not a later phase
Tool permissions, injection defenses and PII handling are set while the system is being built.
Cost is an engineering metric
Cost per task is tracked alongside latency and accuracy from the first prototype.
Your team owns the result
Documented architecture, handover and code your engineers can maintain without us.
Next step
Have an AI problem to solve? Let's talk.
Bring the workflow, the constraints and the data. We will tell you what is realistic, what it costs and how we would build it.