Put Generative AI into Production
Every company is experimenting with AI — far fewer have anything running in production. Pilots stall, costs spiral, and no one can vouch for what the model will say. The gap is rarely the model itself; it's the operational framework around it. Stratto builds production-grade generative AI on Amazon Bedrock: guardrails, private data, predictable performance, and the right model for the job — Claude, Amazon Nova, or OpenAI, all running natively on Bedrock.
Pilots Everywhere. Production Nowhere.
Deloitte's State of AI in the Enterprise 2026 survey found that only 25% of organizations have moved even 40% of their AI experiments into production. The demos work; the deployments don't — and the cause is rarely the model. It's data readiness and the operational framework around it: prototypes that never harden, unpredictable behavior, and unanswered privacy and cost questions.
Pilot Purgatory
A weekend demo impresses everyone, then dies on the vine. Without a platform, data pipeline, or evaluation process, every prototype has to be rebuilt from scratch to reach production — so it never does.
Unpredictable Behavior
The model hallucinates, drifts off-topic, or answers questions it shouldn't. Without guardrails, grounding, and evaluation, no one can promise what it will say to a customer — so it never ships to one.
Data & Cost Risk
Where does your data go? Will it train someone else's model? What happens when token spend triples overnight? Unanswered, these questions keep AI stuck in the sandbox instead of the business.
Model Matters. The Framework Matters More.
Stratto Technologies builds generative AI on Amazon Bedrock — one operational framework for guardrails, private data, and predictable performance — while staying model-agnostic: Claude, Amazon Nova, and OpenAI models all run natively on Bedrock. We pick the best model for each job, then engineer everything around it that makes AI safe to depend on.
The industry obsesses over which model is best this month. In production, the model is one component. What determines whether AI is trustworthy is everything around it: how it's grounded in your data, how it's constrained by guardrails, how its cost is controlled, and how its quality is measured over time.
That's why we standardize on a framework, not a model. Change the model whenever a better one arrives — the guardrails, evaluations, and operations stay in place.
Guardrails & Safety
Content filtering, topic boundaries, and denied-topic controls so the system stays on-mission and never says what it shouldn't — enforced at the platform level, not left to prompt luck.
Your Private Data (RAG)
Retrieval-augmented generation grounds every answer in your knowledge base, documents, and systems. The model reads your data at query time — it never trains on it.
Predictable Cost
Model routing, caching, request budgets, and per-feature token observability. You know what every AI workflow costs before it ships — and it never surprises the invoice.
Model Choice
Claude, Amazon Nova, and OpenAI models all run natively on Bedrock. We match the model to the task — reasoning, speed, or cost — and swap it without re-architecting.
Evaluation & Quality
Automated evals catch regressions before users do. We measure accuracy, groundedness, and safety continuously, so quality is a number you can track — not a hope.
Security & Compliance
Data isolation, access controls, encryption, and full audit logging — built on AWS, aligned with the compliance requirements of regulated industries.
From AI Strategy to Systems in Production
Stratto Technologies builds the full range of production generative AI: strategy and innovation, retrieval assistants grounded in your data, autonomous agents, intelligent document processing, and the AI-Ready Platform that everything else runs on.
AI Strategy & Innovation
We partner with you to reimagine business processes — from idea, to building, to delivering new products and services. Identify where generative AI creates real value before writing a line of code.
Knowledge Assistants (RAG)
Chat and search over your own documents, wikis, and systems. Grounded answers with citations — for support, sales enablement, internal knowledge, and customer self-service.
AI Agents & Automation
Agentic workflows that take action across your systems — triaging, routing, drafting, and executing multi-step tasks with human approval where it matters.
Custom Copilots
Domain-specific assistants embedded in your products and internal tools — trained on your workflows, integrated with your data, and tuned to how your teams actually work.
Intelligent Document Processing
Extract, classify, and summarize at scale — contracts, claims, invoices, clinical notes. Turn unstructured documents into structured, actionable data.
AI-Ready Platform
The foundation the rest is built on: secure data pipelines, vector store, guardrails, prompt and model management, evaluations, and observability. Build it once — every future feature ships faster.
One Use Case at a Time, All the Way to Production
Stratto Technologies works in four stages — discover, prototype, harden, operate — proving value on one high-impact use case before scaling. It's the same disciplined, AI-assisted methodology we use to build our own platforms.
Discover
We map your processes and data to find where generative AI creates real, measurable value — and where it doesn't. You leave with a prioritized use-case shortlist.
Prototype
We build one high-value use case end to end on your real data in weeks — enough to prove the value and expose the hard parts early.
Harden
Guardrails, evaluations, security, and cost controls turn the prototype into a system you can put in front of customers with confidence.
Operate
We run it in production — monitoring quality, cost, and drift — and extend the AI-Ready Platform so the next use case ships faster.
We don't vibe-code production AI. Our disciplined AI methodology — persistent context, planned execution, and specialized agents — is how we ship reliable systems, and it's the same rigor we bring to yours.
Want to prove it first? The fixed-price AI Deployment Sprint takes one workflow to a working pilot in about 30 days. This practice is what that pilot graduates into — the platform, the hardening, and the production system, scoped per engagement.
Built for Companies That Take AI Seriously
Our generative AI service is designed for organizations ready to move past experimentation — teams with real data, real workflows, and a real need for AI that behaves predictably in front of customers and regulators.
Scoped per stage. Approved at every gate.
Each stage is scoped and priced at the gate before it — you approve every step, with no open-ended commitment. Enter anywhere: from strategy, from an existing pilot, or from a completed Deployment Sprint.
Common Questions
What mid-market teams ask before putting generative AI into production with Stratto Technologies.
Move AI from the sandbox to the business
Tell us the use case you've been trying to ship. We'll show you what it takes to put it into production — safely, predictably, and on your own data.