Available for new engagements

Production AI Systems for Startups

We build LLM pipelines, RAG systems, and multi-agent workflows that actually hold up in production. For startups that need AI infrastructure built to last, not just to demo.

30 minutes · no deck · you leave with an opinion on your architecture

// production RAG pipelinelive
01queryuser input
02hybrid retrievalvector + BM25
03rerank + guardrailsprecision pass
04LLM + eval harnessscored output
05responseto your app
traces · latency · token cost · eval metrics

Teams we've shipped with

HisabKitab
Discodog
FixMyAir

16+

AI systems taken from prototype to production

4 wks

Median time from kickoff to first production release

35-40%

Reduction in inference cost after rebuild

Most AI builds fail in production. Here's why.

It's more common than you'd think.

01

The Demo Gap

It works in a notebook. Then real users, real data, and real load show up. Most AI prototypes are built to demo well, not to survive contact with production.

02

The Architecture Problem

Retrieval that works on 100 documents breaks on 100,000. Agents that behave in testing hallucinate in production. Making AI reliable is a fundamentally different engineering problem than making it work at all.

03

The Expertise Gap

Most engineering teams aren't specialists in LLM systems. Production AI requires deep knowledge of retrieval, inference optimization, eval frameworks, and observability. That expertise takes years to develop.

01

RAG & Retrieval Systems

Production retrieval pipelines with hybrid search, re-ranking, evaluation, and observability. For startups where the accuracy of answers actually matters.

02

Multi-Agent Workflows

Autonomous AI systems that coordinate tasks across multiple specialized agents, with proper state management, error recovery, and monitoring baked in.

03

LLM Infrastructure

The backend your AI product runs on: inference optimization, cost controls, caching, streaming, and observability. Built to hold up under real load.

04

AI Architecture Consulting

A focused engagement before you start building. We design the system, surface the risks, and hand off a build plan your team can actually execute.

Why teams choose us

Engineering depth

LLM orchestration, RAG pipelines, multi-agent architectures. Not just proofs of concept.

Stack fluency

LangChain · LangGraph · LlamaIndex · Chroma · Pinecone · pgvector · Anthropic · OpenAI.

Startup velocity

We move at startup speed without cutting engineering corners.

How it works, start to handover.

Four stages. You know the cost and the shape of the system before the build starts.

30 minutes

We find out whether we're the right fit

You tell us what you're building and where it's stuck. We tell you plainly whether this is a two-week fix, a three-month build, or something you shouldn't be doing with AI at all.

You leave with: An honest read on your architecture and a rough range.

1-2 weeks

We design the system before anyone writes it

We map the data, choose the stack, define what "working" means in numbers, and write the plan down. Then we price the build against that plan. So, the number doesn't move later.

You leave with: An architecture doc, an evaluation plan, and a fixed build quote.

4-10 weeks

We build it on your real data

Weekly demos against your actual documents and queries, with the evaluation scores next to them. You see the system getting measurably better, not a status update saying it is.

You leave with: A deployed system, monitored, with costs you can predict.

1 week

We hand it over and get out of the way

Documentation, dashboards, the evaluation suite, and a walkthrough with whoever maintains it next. No black boxes, no retainer you can't leave. You own all of it.

You leave with: Full ownership, and us on call if you want us.

What founders say afterwards

“What stood out was their sense of ownership. They were proactive, accountable, and genuinely committed to getting the project right.”

Yegs

Founder, Lexxy AI

“Working with Accelate has been a great experience. They transformed our vision for FixMyAir into a powerful AI-driven product. Their technical expertise, problem-solving, and commitment make them feel like a trusted technology partner, not just an agency.”

John Berardino

Founder, FixMyAir

Building AI into your product and need something that actually ships?

Thirty minutes, no deck, no pitch. If we're not the right team for it, we'll say so and point you somewhere better.

Book a Discovery Call