AI integrations, data engineering, and enterprise infrastructure — built by engineers who ship production systems, not pitch decks.
Most companies know they need to do something with AI. The hard part is knowing what's real, what's hype, and who can actually build it.
New AI tools launch every week — LLMs, agents, RAG, MCP. You need a guide who can cut through the noise and tell you what actually applies to your business.
Your current IT provider handles the basics. But when you ask about AI integration or custom automation, they don't have the answer.
You have data, processes, and ideas — but no clear path from "we should use AI" to something running in production and generating value.
We bridge the space between AI capabilities and the systems they run on — so you're not juggling three vendors to get one thing working.
Production-grade LLM integrations, retrieval-augmented generation pipelines, and AI-powered data transformations at scale. Moving from "we tried ChatGPT" to something that generates measurable business value.
ETL/ELT pipelines, data warehouse architecture, ML model training and deployment, and BI reporting. If your data is scattered and nobody can get a straight answer out of it, this is where we start.
Full M365 ecosystem management, Azure IaaS, Microsoft Copilot and AI Foundry deployment, domain and email migrations, and technology integrations for acquisitions. The Microsoft stack, done right.
Zero trust architecture, EDR, SIEM, on-premises server deployment, enterprise networking, and business continuity and disaster recovery. AI is only as good as the foundation it runs on.
MCP server development, REST API design, OAuth/OIDC/SAML authentication, and ad hoc application creation. We build the connective tissue between your AI systems and your existing software.
Before launching Stone Bird, our team built production AI systems that moved the needle — measurably.
For a mid-size e-commerce company, we designed and deployed an LLM-powered product content system from scratch — data warehouse, ML models, production pipelines, the entire stack.
The result: $3M in directly attributable new revenue, with architecture designed to scale across the full catalog to $30M. Not a proof of concept. Production revenue, measured and proven.
We're a new company, but we're not new to this work.
We work best with companies that have real operations, real data, and a real desire to put AI to use — not just talk about it.
15 minutes, no obligations. Tell us what you're working with and we'll tell you honestly whether we can help.
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