ORIJINS · CONSULTING

Strategic AI Transformation, Done Right.

Eighty-seven percent of enterprise AI projects fail. Most consulting firms can't tell a fine-tune from a function call. We're the operators they should have hired in the first place. We don't write decks. We ship working systems. Then we leave.

87% · AI projects fail
12 weeks · to working code
0 · decks shipped

AI consulting is broken — and the bills are still being sent.

A boardroom mandate gets handed to a Big Four consultancy. Eighteen months and several million dollars later, the deliverable is a two-hundred-slide deck and a "phase 2 scoping engagement". Nothing ships. The CEO is told the failure was "change management". The market has been doing this for three years now. It's time to stop pretending it works.

0%
AI Project Failure Rate
87% of enterprise AI initiatives fail to make it from pilot to production. The most common cause is not technology — it is consultants who don't understand the underlying systems they're scoping.
Source: BCG, "Where's the Value in AI?", 2024
$0B / yr
Wasted on AI Consulting
Enterprises will spend roughly $50 billion this year on AI strategy and integration consulting. Industry analysts estimate over half is spent on engagements that produce no production-grade system.
Source: IDC, Worldwide AI Services Spending Guide 2024
0months avg
Average Engagement
An average enterprise AI engagement runs 14 months from kickoff to first usable system. ORIJINS commitments cap at 12 weeks before something is in production. The same problem. A different ratio.
Source: Gartner Enterprise AI Survey, 2024
0%
Distrust Their AI Vendor
73% of enterprise executives report low or zero trust in the AI vendor they currently work with. Most cite a fundamental gap between the consultant's slide deck and the engineering team's reality.
Source: Deloitte State of Generative AI, 2024

We don't write decks.
We ship working systems.
Then we leave.

— a methodology measured in commits, not slides.

Operator-led AI transformation — engineered, not pitched.

ORIJINS Consulting is staffed by people who have shipped AI systems at scale: GAIA contributors, ex-FAANG engineers, founders who actually built the thing. We bring the team. We embed in your stack. We ship working code. We leave you self-sufficient. That is the whole methodology.

Operator-Led Engagements

Every engagement is led by a senior operator who has personally shipped a comparable system to production. No partners-by-title. No bait-and-switch teams. The person on the call writes the code.

// senior IC · principal-grade only

Working Code in 12 Weeks

Every engagement ships working, in-production code within 12 weeks. Not a prototype, not a sandbox demo. A system serving real users, integrated with your data, monitored, on your repo, owned by your team.

// 12wk SLA · prod-grade by week 12

GAIA Embedded in Workflows

We don't bolt a chatbot to your homepage. We embed GAIA where the work actually happens — claims processing, contract review, sales ops, code review, customer routing — measured by hours saved per FTE per week.

// workflow-native · measurable

Knowledge Transfer to In-House

Every engagement includes a structured handoff: documentation, runbooks, internal training, and a 90-day shadow period where your team owns the system and we step back into advisory. We work to be unnecessary.

// 90-day handoff · knowledge graph

Outcomes-Based Pricing

Most of our fee is contingent on a measurable outcome — hours saved, conversion lift, error rate reduction, latency cut. If the system doesn't move the metric, we don't get paid the back half. It concentrates the mind.

// 40% fixed · 60% on outcome

Open Methodology Library

Every reusable pattern we develop — eval harnesses, RAG architectures, fine-tune playbooks, agentic workflow templates — gets published openly under permissive license. Our methodology is a public good. The work is the moat.

// MIT-licensed · public github

$3.4M in slides vs. $480K in shipped code.

A side-by-side. Same enterprise. Same problem statement. Same target outcome. Two different theories of what "consulting" should mean. Numbers from real, anonymized engagements observed in 2024–2025.

Big Four AI strategy engagement— 14 months, 22 consultants, 187-slide deliverable
$3.4M
100% — and zero systems shipped to production
Boutique AI consultancy— 9 months, 8 consultants, two pilots, no production system
$1.2M
35% — pilots that never crossed the valley
ORIJINS Consulting · 12-week engagement— 4 senior operators, in-production system, knowledge transfer, runbooks
$480K
14% of the cost — and a working system on day 84

The Big Four engagement produced a deck. The ORIJINS engagement produced a system that — in one anonymized case — saved 110,000 FTE-hours per year. The cost ratio was 7×. The outcome ratio was infinite. The work is not the same work.

By 2050, AI transformation is routine engineering — not a billion-dollar gamble.

We are building toward a future where deploying AI inside an enterprise is as normal, predictable, and unspectacular as deploying a database was in the 2010s. A roadmap measured in production systems shipped, not pitches won.

2026 · Now
First 12 enterprise engagements live
Twelve in-production engagements across financial services, healthcare, logistics, and government. Each one with a published case-study, an open methodology, and a measurable outcome — not a marketing testimonial, an audit-grade number.
2028
100 operators. 60 active engagements. Open playbooks.
A senior operator bench of 100, all of whom have shipped a comparable AI system to production. The Open Methodology Library reaches 60+ public patterns covering RAG, evals, agentic systems, fine-tuning, and observability.
2032
Outcomes-based becomes the industry default
The "deck-and-disappear" consulting era ends. Enterprise procurement standardizes on outcomes-based AI engagement contracts. Consultants are paid for systems that move metrics, not for hours billed against retainers.
2040
10,000 operators. The Big Four shrink.
A global network of 10,000 senior AI operators — all working on outcomes-based engagements, all publishing methodology openly. The McKinsey/Bain/BCG/Big Four AI practices contract by half as their core moat (access) is replaced with proof (shipping).
2050
AI transformation is just engineering.
Deploying GAIA-class systems inside an enterprise is a normal, predictable, multi-week project. The phrase "AI transformation engagement" sounds as quaint as "ERP transformation" did in 2024. Building works again. Talking about building has finally become unfashionable.

Brief us on the real problem.

If you're a leader who has lost faith in glossy decks, who needs an AI system in production within a quarter, who values working code over working theater — we're the right team to call. Drop your email. We respond within 48 hours, with a senior operator, not a salesperson.

No spam. A senior operator replies within 48 hours.