# The Agency

Senior forward-deployed engineers and AI consultants embedded with your team to design, build, and ship production software and AI systems.

![](https://devzilla.co/_astro/studio-late-shift.CtJv8uIY_1DrxFi.jpg)

Forward-Deployed Engineering & AI Consulting

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

### [AI Product Strategy](https://devzilla.co/services/forward-deployed-ai-engineering/)

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](https://devzilla.co/services/forward-deployed-ai-engineering/)

### [Full-Stack Product Engineering](https://devzilla.co/services/ai-prototype-to-production/)

Design and production engineering for web platforms, internal tools, and data-heavy products. Senior crew only. No handoffs to a bench.

[Read the capability](https://devzilla.co/services/ai-prototype-to-production/)

### [Agent & LLM Systems](https://devzilla.co/services/agent-and-llm-systems/)

Retrieval pipelines, agent orchestration, evaluation harnesses, and cost engineering. The unglamorous 80% that makes AI features reliable.

[Read the capability](https://devzilla.co/services/agent-and-llm-systems/)

### Data Engineering

Pipelines, warehouses and lakehouses, dataset quality, and the unglamorous plumbing that makes AI work. Data your team can actually trust.

### [Geospatial Systems](https://devzilla.co/services/geospatial-systems/)

Location intelligence, spatial data pipelines, and mapping products. When where something happens is half the problem, we speak the language.

[Read the capability](https://devzilla.co/services/geospatial-systems/)

### [Knowledge Graph Systems](https://devzilla.co/services/knowledge-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 capability](https://devzilla.co/services/knowledge-graph-systems/)

Direct 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

1.  ### Frame the system
    
    Define the outcome, users, source systems, failure cost, ownership, and constraints before selecting a model or vendor.
    
2.  ### Build in context
    
    Work in the client repository, data environment, review process, and deployment target so production constraints appear early.
    
3.  ### Evaluate and release
    
    Measure quality, failure behavior, latency, and cost against explicit acceptance criteria, then release in controlled stages.
    
4.  ### 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 →](https://devzilla.co/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 →](https://devzilla.co/contact/)

Canonical URL: https://devzilla.co/agency/