AI-native product engineering

We engineer software for the AI era.

Datricx AI designs, builds, and scales AI-powered products — GenAI applications, autonomous agents, and data platforms grounded in your data. From first prototype to enterprise production.

Products shipped to market
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Products shipped to market

Industries served
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Industries served

Client retention rate
0%

Client retention rate

To first working demo
0 wks

To first working demo

Trusted by product teams across four continents

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5.0 client rating

Rated five stars across review platforms

Top Rated AI Engineering Company

Recognized for AI delivery excellence, 2026

100% recommendation rate

Every reference client would hire us again

Security-first delivery

SOC 2, HIPAA & GDPR-conscious engineering

Why Datricx

Everyone is talking about AI.
Few are shipping it.

Most AI projects die between the demo and production. Datricx exists for that gap — a product engineering partner with the discipline to take intelligent software all the way to real users, real scale, and real returns.

01

AI-first, not AI-washed

Every engagement ships with evaluation harnesses, observability, and guardrails — because AI you can't measure is AI you can't trust.

02

Senior teams only

No junior benches, no bait-and-switch staffing. The engineers you meet in the first call are the engineers writing your code.

03

Outcomes over output

We scope against business metrics — conversion, cost per ticket, time to close — and report against them every single week.

How we work

The Datricx Loop — evidence before investment.

A delivery method built for the AI era: prove value in weeks, scale only what the numbers justify, and never bet a roadmap on a demo.

  1. Week 0–1

    01Discover

    A focused discovery sprint: we map the problem, audit your data and systems, and rank opportunities by ROI and risk. You leave with a scoped plan and a number attached to it.

  2. Week 1–3

    02Prove

    A working proof of value on your real data — not slides. Evaluation harness included, so the go/no-go decision is made on evidence.

  3. Week 3–10

    03Build

    Senior squads ship in weekly releases. Every sprint ends with a demo of working software and an honest read on scope, budget, and quality metrics.

  4. Week 10+

    04Ship

    Hardening, security review, load testing, and launch. Observability and runbooks in place before the first real user arrives — not after the first incident.

  5. Ongoing

    05Scale

    Post-launch, we optimize against production reality: model costs, conversion funnels, infrastructure spend. The roadmap keeps compounding.

Industries

Deep in the domains where software decides margins.

SaaS & Technology

Financial Services

Healthcare

Logistics & Supply Chain

Retail & E-commerce

Real Estate & PropTech

Education

Telecom & Media

Technology

Boringly reliable tools,
wielded at the frontier.

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What clients say

Judged by the people
who pay the invoices.

They were the first team that talked to us about evaluation before talking about models. Three weeks in, we had accuracy numbers on our own data — that's when we knew this wasn't another AI vendor selling demos.

Chief Technology Officer

B2B SaaS platform

The squad integrated into our sprints like they'd been here for years. Weekly demos, honest status, and code our own engineers actually want to maintain.

VP of Engineering

Financial services firm

We'd been burned by agencies that shipped a prototype and disappeared. Datricx stayed through launch, tuned costs in production, and the platform has run without a major incident since.

Head of Product

Logistics company

FAQ

The questions every
smart buyer asks.

Anything else? Ask us directly — you’ll talk to an engineer, not a sales script.

Three weeks for a proof of value on your real data, and 8–12 weeks from kickoff to a launched product. We front-load the riskiest assumption so the first thing you see is the thing that matters.

Start a project

Tell us what you
want to build.

Share a few lines about your product or problem. Within one business day, an engineer — not a salesperson — will reply with an honest read and suggested next step.