[ AI DEPLOYMENT COMPANY ][ Forward deployed engineering ]

Ship production AI at startup speed.

We decide what AI is worth building, then we build it. We route every workload to the right model so your runway lasts longer. One team handles everything from strategy to shipped code.

shipline@prod / forward-deployed-ai● canary

We deploy across every major model and never lock you into one

ClaudeOpenAI GPTGoogle GeminiLlamaMistralQwen
01/ 08·The problem//Why now

The math on hiring doesn't work.

Hire a senior AI engineer
$180K/yr
and six months to even find one
  • Your backlog grows while you search
  • Your best engineers get pulled onto it anyway
  • Runway keeps shrinking
Bring us in
Weeks
to AI running in production
  •  A fraction of a full-time hire
  • No hiring delays or FTE risk
  • You keep the code and the knowledge
02/ 08·What we build//Full range

The full range of AI we deploy.

We build everything from simple knowledge assistants to privacy-grade systems most shops won't touch. We scope to what moves your business and skip what doesn't.

01

RAG & knowledge assistants

Answer engines grounded in your own docs and data, with accurate, citable answers.

02

AI agents & automation

Agents that take real actions across your tools and run multi-step workflows.

03

Chatbots & support AI

Customer-facing assistants that resolve, escalate, and stay on-brand.

04

Document & data extraction

Turn contracts, forms, and PDFs into clean structured data.

05

Evals & LLM testing

Harnesses and regression tests so you ship AI changes without breakage.

06

Fine-tuning & custom models

LoRA/QLoRA and adapters when off-the-shelf models aren't enough, or cost too much.

07

Voice & speech AI

Transcription, voice agents, and speech interfaces wired into your product.

08

Privacy & on-device AI

Privacy-preserving, federated, and on-device deployments for sensitive data.

03/ 08·How we work//One pipeline

Embedded engineering, from one team.

We don't hand over a strategy deck and walk away. Our engineers work inside your team and help ship AI into production alongside you, from deciding what's worth building to running it day to day.

ConsultancyDiscovery
A short diagnostic. We map your workflows and tell you which two or three are worth building AI for, and which aren't.
fixed scope
StudioDeployment Sprint
A focused 2–4 week engagement to take one workflow into production.
2–4 weeks
StudioEmbedded
Day-to-day embedded engineering: our engineers work inside your team and ship alongside you.
monthly retainer
StudioManaged Ops
Once your AI is live: monitoring, regression evals, and continuous model-cost optimisation.
ongoing
Applied Research
For harder problems: privacy-preserving and federated deployments, custom evals, on-device AI.
project / grant
04/ 08·Our stack//Model-agnostic

The tools we deploy with.

We stay model-agnostic across every layer and choose the stack that fits your workflow and your runway.

Models
ClaudeOpenAI GPTGoogle GeminiLlamaMistralDeepSeekQwenKimiGLM
Cloud & infra
AWSAzureGoogle CloudModalDockerKubernetes
Orchestration
LangChainLlamaIndexLangGraphDSPyOpenClawNemoClawn8n
Data & processing
DatabricksApache SparkApache FlinkSnowflakePineconeWeaviatepgvectorQdrant
Inference & serving
vLLMOllamaBedrockVertex AITogetherGroq
Ops & evals
LangSmithLangfuseWeights & BiasesRagas
Guardrails & privacy
NeMo GuardrailsPresidioDifferential privacyFederated learning
Compute & hardware
NVIDIAAMDDGX SparkRTXAndroidiOSMac
05/ 08·Why us//Built for runway

Built for runway.
No lock-in.

01

Embedded, not hands-off

Our engineers work inside your team and ship alongside you. There's no handoff and no slide deck that goes nowhere, just production code you own.

02

No vendor lock-in

Model-neutral by design. We route to the cheapest model that does the job, so your token bill doesn't outrun your growth.

03

You own the outcome

We transfer knowledge and leave you with maintainable systems, not a black box that depends on us.

04

We handle the hard stuff

A team that takes on the privacy-sensitive and research-grade problems generalist shops turn away.

06 / 08·How an engagement runs//Process

From first call to live in production.

A clear path, not a black box. Most engagements start with Discovery and move through to AI running in your product.

01

Discover

We map your workflows and pin down the two or three worth deploying AI into.

02

Scope

A fixed-scope plan for one workflow: the model, the architecture, the success metric.

03

Build & ship

Our engineers work inside your team and take it to production in weeks. It gets tested and evaluated before going live.

04

Hand over

You get the code, the docs, and the knowledge. Run it yourself, or keep us on for ops.

07 / 08·What you get//Deliverables

What's in your hands at the end.

There are no black boxes and no lock-in. Everything we build is yours to run, change, and own.

Production AI, deployed

A working system live in your environment, not a prototype or a proof of concept.

Source code you own

Clean, documented, maintainable code in your repository. No proprietary wrapper.

An evaluation harness

Tests and metrics so you can change models or prompts later without breaking things.

Knowledge transfer

Your team understands how it works and how to extend it. We don't leave you dependent on us.

A model-cost view

Clear picture of what each workload costs to run, and where it can be optimised as you scale.

A path to what's next

An honest read on the next workflow worth deploying, or whether you even need us again.

08 / 08·How we operate//Principles

How we operate.

The commitments behind every engagement.

01

Model-agnostic, always

We pick the model that fits the workload and your budget: Claude, GPT, Gemini, or open source. We're never tied to one vendor.

02

You own everything we build

Code, docs, and knowledge transfer at handover. We build to leave you independent, not dependent.

03

We ship, we don't just advise

Our people work inside your team and put working AI into production alongside you.

04

Honest about what's worth it

If a workflow isn't worth deploying AI into, we'll tell you. We'd rather scope less and ship what matters.

Tell us what you're trying to ship.

A 30-minute call. We'll tell you straight whether a sprint can get it to production, and roughly what it would cost.

Book a discovery call