AI engineering,

actually shipped.

We embed senior AI engineers inside your organization. They join your Slack, commit to your repo, and don't leave until it's in production.

Claude 3.5 SonnetReasoning
GPT-4oMultimodal
Gemini 1.5 ProLong-context
LangChainOrchestration
LlamaIndexRAG
pgvectorVector store
Mistral 7BOn-premise
Llama 3Fine-tuning
PineconeEmbeddings
WeaviateSemantic search
OpenAI o1Complex reasoning
Cohere Command R+Enterprise RAG
Claude 3.5 SonnetReasoning
GPT-4oMultimodal
Gemini 1.5 ProLong-context
LangChainOrchestration
LlamaIndexRAG
pgvectorVector store
Mistral 7BOn-premise
Llama 3Fine-tuning
PineconeEmbeddings
WeaviateSemantic search
OpenAI o1Complex reasoning
Cohere Command R+Enterprise RAG

The problem

Most AI projects
never see daylight.

87% of machine learning models never make it to production. Not because the technology isn't good enough — because building AI that survives contact with reality is a different skill than building AI in a notebook.

The gap is execution. And execution is a people problem.

Consulting

Decks, not deploys

Traditional firms deliver strategy. Six months and $200k later, you have a framework and a recommendation to hire.

Staffing

Engineers without context

Agencies send developers who spend the first three months understanding your domain instead of building in it.

Internal POCs

Staging-ward bound

In-house proofs-of-concept impress in demos then quietly die because no one owns taking them to production.

Services

What we do,
concretely.

01

Embedded AI Teams

A dedicated team of senior AI engineers joins your organization — in your Slack, in your standups, committed to your repo. They own the problem end-to-end, from data to deployment.

LLMsRAG SystemsML PipelinesModel Serving
3–12 months
02

AI System Architecture

Before you write a line of code, we design the right system. Data ingestion, vector stores, fine-tuning strategy, evaluation frameworks, monitoring. A blueprint you can build with confidence.

System DesignEvaluationInfrastructure
4–6 weeks
03

Rapid Deployment Sprints

A single use case, fully built and deployed in two weeks. Real users, real data, honest results. The fastest way to know if an AI investment is worth making.

PrototypingUser TestingGo/No-Go
2 weeks
04

AI Capability Building

We don't just build the thing — we make sure your team can own it. Hiring support, internal training, tooling setup, and the processes that keep AI systems healthy after we leave.

HiringInternal TrainingDocumentation
Ongoing

How it works

From kickoff to
production.

No months-long onboarding. No hand-off theater. Our engagement model is built around one thing: getting your AI running in the real world.

Week 1–21

Embed & align

Our engineers join your Slack, get repo access, and run discovery sessions. By end of week two we have a shared definition of success and a technical roadmap.

Week 3–82

Build & ship

We write code. Real code, in your codebase. Weekly demos with real users — not slides. We adapt fast based on what the data and users tell us.

Week 9–123

Harden & hand off

We stress-test for production, document everything, and work alongside your engineers until ownership is fully transferred. You end up stronger than before we arrived.

Week 1
Week 12

Lab partnerships

Deep partnerships
with the frontier.

We work directly with the labs building today's best models — and engineer the systems that make them work at enterprise scale.

That means you get engineers who understand model behavior at a deep level, not just API wrappers.

Anthropic
Claude — reasoning, safety, enterprise AI
OpenAI
GPT-4o, o1 — multimodal and agentic systems
Google DeepMind
Gemini — long-context and multimodal workloads
Mistral AI
Open-weight models for on-premise deployment
Cohere
Command — enterprise RAG and semantic search
Meta AI
Llama — fine-tuning and open-source LLM ops

Why Trida AI

Built for builders.Hired for results.

We started Trida AI because too many AI projects fail not from lack of ideas, but from lack of execution. Every principle below exists because we've lived the alternative.

Senior engineers only

Every FDE has shipped AI to production. No juniors, no PMs pretending to code.

Outcome-based pricing

We price against business outcomes, not hours. No milestone = no invoice.

Opinionated, not dogmatic

We have strong views on what works, we'll tell you when an approach is wrong, but adapt to your constraints.

Knowledge transfer by default

Everything we build, your team understands. Docs, training, pair-programming until ownership is clear.

Full-stack AI capability

Data pipelines to model training to APIs to UI. No finger-pointing between vendors.

Week-one start

Within a week, our engineers are writing code in your repo.

Get started

Let's build
something real.

Tell us about your toughest AI challenge. We respond within 24 hours with an honest opinion — not a sales pitch.

Response within 24 hours — from an engineer, not sales
Free 45-minute technical scoping call
Honest assessment of whether AI is right for your use case

Start your engagement

Ready to ship AI?

Tell us what you're building. We respond within 24 hours — from an engineer, not sales.

Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate · Build · Ship · Scale · Deploy · Iterate ·