Practical AI engineering for organizations that need results, not hype.
The Stack Research Corporation applies knowledge in generative AI, security, and infrastructure. We design and build solutions that work in production.
Core capabilities
We work on high-impact problems where AI and infrastructure meet. The goal is simple: systems that behave predictably under real load, with clear operational ownership.
Task-specific agents integrated with your tools, APIs, and access controls, designed to work alongside your existing teams.
Debugging brittle pipelines, latency spikes, failure modes, and edge cases in deployed AI systems—under real-world data and traffic.
Opinionated AWS patterns for AI workloads: networking, storage, security, and deployment architectures that avoid fragile one-off setups.
Automation for detection and response, plus threat models that include AI-specific risks, abuse paths, and data exposure.
Independent assessment of vendor claims, architectures, and teams for acquisitions, compliance audits, or large internal bets.
Clean interfaces between AI components and the rest of your stack—APIs, workflows, and observability that your engineers can own.
Who we work with
We're not a general-purpose agency. We work with teams that have clear stakes and real constraints.
CTOs evaluating AI investments and needing an objective view of feasibility, cost, and operational impact.
Teams stuck on implementation details—retrieval quality, latency, reliability, or integration with existing systems.
Security officers automating threat detection and modeling AI-specific risks across their environment.
Infrastructure directors scaling AI workloads while keeping costs, reliability, and observability under control.
Investors and acquirers needing grounded technical assessment of AI products, teams, and claims.
Organizations prioritizing substance over marketing, and willing to hear when AI is not the right tool.
Why Stack Research
The AI landscape is full of promises and slide decks. Our value is in accurate assessment and systems that behave the way you expect.
If AI isn't the answer, we say so early. The objective is solving your problem, not justifying a technology choice.
We design for runbooks, dashboards, and on-call engineers—not conference talks.
Opinionated about infrastructure. We steer you toward proven AWS patterns, not theoretical architectures.
You work directly with the core team. No unnecessary layers or relays.
Recommendations are based on engineering reality and experience, not vendor promises.
Every engagement produces complete technical documentation so your team is more capable when we leave.
How we work
Two straightforward modes of engagement, both designed to produce concrete artifacts and operational clarity.
Fixed-fee, fixed-timeframe assessments with clear deliverables: architecture review, risk analysis, and prioritized recommendations. You get a realistic picture of what will work, what won't, and where to invest next.
Time-and-materials implementation alongside your team. We adapt as requirements evolve—debugging, building, and documenting until the system is ready for handoff.
Get in touch
We work with a limited number of clients at a time. If you have a specific AI or infrastructure problem and want a direct technical conversation, send a short note describing the situation.
mail@stackresearch.org