AI Product Strategy
Where AI actually belongs in your product, what it costs, and what it breaks. A roadmap grounded in Lab research, not vendor decks.
Read the capability
Forward-Deployed Engineering & AI Consulting
The Agency
Hire a forward-deployed engineer. We embed senior engineers and AI consultants straight into your team, and build production software and AI systems like they carry our name, because they do.
Services
What we build with client teams
Full-Stack Product Engineering
Design and production engineering for web platforms, internal tools, and data-heavy products. Senior crew only. No handoffs to a bench.
Read the capabilityAgent & LLM Systems
Retrieval pipelines, agent orchestration, evaluation harnesses, and cost engineering. The unglamorous 80% that makes AI features reliable.
Read the capabilityData Engineering
Pipelines, warehouses and lakehouses, dataset quality, and the unglamorous plumbing that makes AI work. Data your team can actually trust.
Geospatial Systems
Location intelligence, spatial data pipelines, and mapping products. When where something happens is half the problem, we speak the language.
Read the capabilityKnowledge Graph Systems
Knowledge graphs and graph-database systems built for real operations, including graph-backed agent memory and company-brain platforms that keep institutional knowledge durable.
Read the capabilityDirect answer
What is a forward-deployed AI engineer?
A forward-deployed AI engineer works inside the client team instead of handing requirements to a remote queue. Devzilla engineers build in the real stack, own technical decisions through deployment, and leave the client with documented software and operating knowledge the client can continue without permanent agency dependence.
Why teams hire us
Built like we
own it.
Forward-deployed
We embed senior engineers directly in your team, in your stack and your standups. Not arm’s length over a ticket queue.
AI, actually applied
Consulting grounded in Lab research, not vendor decks. We tell you where AI belongs, what it costs, and what it breaks before you build it.
Fixed, honest scopes
Clear deliverables and kill criteria. We tell you when to stop paying us.
Yours to run
Everything we build is documented, explained, and handed over completely. You own the system, and you are never dependent on us to keep it alive.
Engagement process
How the work moves
Frame the system
Define the outcome, users, source systems, failure cost, ownership, and constraints before selecting a model or vendor.
Build in context
Work in the client repository, data environment, review process, and deployment target so production constraints appear early.
Evaluate and release
Measure quality, failure behavior, latency, and cost against explicit acceptance criteria, then release in controlled stages.
Transfer ownership
Document the architecture and decisions, explain the operating paths, and leave the client able to run and extend the system.
Public evidence
Inspect what Devzilla built
Company-owned systems show how Devzilla handles government sources, geographic boundaries, data pipelines, deployment, and operational tradeoffs. They are demonstrations, not client case studies.
Explore the work →FAQ
Frequently asked questions
What is a forward-deployed AI engineer?
A forward-deployed AI engineer embeds with the client team, builds in the real stack, owns technical decisions through deployment, and transfers the working system and its reasoning to the client.
How is Devzilla different from an ordinary consultancy?
Devzilla remains accountable for implementation and production behavior. Strategy must become architecture, code, evaluation, deployment, or a clear recommendation to stop.
Does the client own what Devzilla builds?
Yes. Client engagement terms govern the specific work, and the delivery model is designed around complete documentation, knowledge transfer, and client operational ownership.
Can Devzilla start from an existing AI prototype?
Yes. The first step is to identify what the prototype proves, what it avoids, and what evaluation, data, security, cost, and operational work is still required.
Bring us the hard one.
The ambiguous, the stalled, the ambitious. That is the work we want.
Start a project →