For Investors · Frontier Labs · Consultancies · Industrial Primes
SaaS is dead.
What comes next is DaaS.
Deployment as a Service
Software sold access and called it value. The AI economy will not get away with that in the physical world. A model subscription doesn't survive contact with a factory floor. The value goes to whoever can industrialise deployment. This page is the case for being part of that with us.
The Problem Everyone Can Now See
The AI industry has an adoption story and a deployment problem.
MIT's 2025 NANDA research found that 95% of enterprise generative-AI pilots deliver no measurable P&L impact, and located the failure not in the models but in organisational integration. Our own work inside manufacturing says the same thing in plainer words: demos get called deployments. Proof-of-concepts run for years with no security model, no economic validation, and no operational integration.
The models keep getting better. The deployment gap doesn't close by itself. It is a discipline problem, and disciplines need measurement.
Adoption is a purchasing decision. Deployment is an engineering achievement. The industry keeps billing for the first and promising the second.
What AIRL Is
A readiness standard, not another maturity survey
AIRL™, the AI Readiness Level framework, measures an organisation's capability to deploy AI at economic scale: 9 levels, 4 stages (Concept → Development → Demonstration → Production), each level gated by evidence, not self-assessment. Progress is measured in QCDS: quality, cost, delivery, safety. The language operations already runs on.
The lineage is deliberate: NASA's Technology Readiness Levels, MCRL, PAS 1040, ISO 56000. Readiness levels work because everyone means the same thing by them. That is also why AIRL is trademarked: a level only functions as a standard if its definitions can't drift, and a standard only holds if someone is accountable for it. The mark protects the meaning, so an "AIRL 7" in a contract is worth something.
Born in manufacturing, the hardest deployment environment there is. Built for the real world beyond it.
The Model
Deployment as a Service
01
Assess
The AIRL assessment establishes where an organisation actually is: level by level, dimension by dimension. Not where the vendor deck says it is.
02
Contract on levels, not seats
DaaS engagements are scoped as movement through gate criteria: take this line from AIRL 3 to AIRL 6, evidenced in QCDS. The deliverable is a deployment, not a licence. That is the structural break with SaaS: value priced on outcomes the customer can audit.
03
Delivered by Manufacturing Engineers
Not management consultants. Not IT consultants. People who have stood on the floor a deployment has to survive. The framework is the product; the engineering discipline is the moat.
Who We Want In The Room
Four kinds of partner
Investors & VCs
The assessment platform, the certification model, and the DaaS delivery network all scale beyond one practice. If your thesis is that AI value shifts from model access to deployed outcomes, we are the measurement layer that thesis needs.
Frontier Labs
Your models are ready for the physical economy before the physical economy is ready for them. AIRL gives your enterprise customers a readiness standard, and an honest answer to "why did the pilot stall?" that isn't about your model.
Big Four & Consultancies
Your clients are stuck between adoption and deployment, and slideware won't move them. License the methodology. Bring the client relationships; we bring the framework and the gate discipline.
Industrial Primes
If you run factories, AIRL is how you stop paying for adoption theatre. Assess the estate, contract improvement on levels, and hold every vendor to gate criteria.
The Ask
We are early, deliberately.
The standard is being written now.
If any of the four seats above sounds like yours, start a conversation. One email, no deck required. Tell us who you are and which seat.
Dr M Verma · Kaipability Ltd · This page is an invitation to a conversation, not an offer of securities.