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Solve business problems with the AI & ML expertise of Zutrax.
A one-stop shop for businesses using AI/ML with cloud-native solutions: RAG pipelines, MCP-based agent tooling and custom model tuning, from prototype through production and ongoing operation.
What we build
Generative AI, engineered like production software
We treat AI development like the rest of your stack: assessed, architected, tested and deployed with the rigor of any mission-critical system, then monitored and tuned after launch.
AI Strategy & Readiness
We assess your data, infrastructure and use cases to find where generative AI creates real business value, and where it doesn’t yet.
RAG & Custom LLM Applications
Retrieval-augmented generation pipelines built on your own data, connected to the model provider that fits your latency, cost and accuracy needs.
Agent & MCP Tooling
Agentic workflows and Model Context Protocol integrations that let AI systems safely take action inside your existing tools and data.
Model Fine-Tuning & Evaluation
Custom model tuning against your domain data, with evaluation harnesses that catch regressions before your users do.
MLOps & AI Deployment
Cloud-native deployment on AWS, Azure and Google Cloud: containerized inference, autoscaling, observability and cost controls from day one.
Enterprise Copilots & Integration
AI features embedded directly into the software you already run, wired into your data, auth and workflows instead of bolted on as a chat widget.
How it works
Agents across a typical organization
Requests arrive through every channel your business already uses, get resolved to the right context, and land in a shared memory your agents can read from. Then the right specialist acts, whether that’s a support reply, a CRM update or a reconciled invoice.
Swipe sideways to see the full diagram.
How we deploy
A deployment lifecycle, not a demo
The same discipline we bring to cloud-native and security engagements, applied to generative AI.
01
Discover
Assess data readiness, integration points and the business case for each candidate use case.
02
Design
Architect the model, retrieval and tooling layer around your latency, cost and compliance constraints.
03
Build & Evaluate
Ship working prototypes fast, with evaluation sets that measure accuracy before anything reaches production.
04
Deploy & Operate
Cloud-native rollout with monitoring, guardrails and cost tracking, plus ongoing tuning as usage grows.
Built on trusted platforms
We deploy against the models you already rely on
Anthropic Claude
OpenAI
Cohere
Google Cloud AI
AWS Bedrock
Azure OpenAI
Bring us a use case. We’ll tell you if it’s ready.
A 30-minute AI readiness call with a clear read on data, scope and effort. No sales deck.