Company
An engineering company for the part of AI nobody demos.
Rainkernel Technologies Private Limited was founded in Hyderabad in September 2026 to build the production layer AI agents are missing. We are young and we say so; what we bring is a published line-up, published prices, open-source engines and a founder who has watched the same pilots stall for years.
Vision
Every AI agent in production carries the evidence that it is reliable, affordable and safe — and the people responsible for it can prove that to an engineer, a CISO, an auditor and a board without a week of improvisation.
Mission
Rainkernel builds the production layer AI agents are missing — evaluation, cost governance, tool attestation and audit-grade records — and delivers it inside our clients' own clouds, at published prices, with acceptance criteria written in numbers. We take pilots to production and keep production accountable.
Values
Six things we will not trade away.
- 01
Evidence over opinion
Every claim on this site has its source one click away, and every deliverable we hand over is a measurement, not a slide. If we cannot put a number on it, we do not sell it.
- 02
Published prices
Nobody in this market publishes a price. We do, for every product, and a quote never exceeds the price on the page for the scope on the page.
- 03
Your cloud, your data, your harness
We deploy inside your estate. Evaluation sets, reports and logs are yours when we leave. We train nothing on client data and we keep no copies.
- 04
Fixed scope, honest exits
Every statement of work has acceptance criteria in numbers, contractual knowledge transfer, IP rights for you and a planned exit — because agents built by a vendor's forward-deployed engineers are being abandoned for the lack of exactly those.
- 05
Open by default
Our attack corpus, evaluation harness and scanner ship as open source. We charge for the attestation, the governance and the evidence — not for hiding the tools.
- 06
Small team, senior hands
A founder-led engineering team in Hyderabad with the engines, the corpus and the rubric already built. Pods plug into integrators as engineers plus toolkit, not as a bench.
How we work
The same five rules in every engagement.
- 01Scope in numbers
One use case, one measurable target, one data source, one channel. The acceptance criteria are agreed before the clock starts.
- 02Inside your cloud
Access to your environment, not copies of your data. Engines and reports run and stay where your data already lives.
- 03Evaluate from day one
A real-case evaluation set and a cost-per-task meter exist before the first prompt is tuned. Every change is scored against them.
- 04Readout, not report-out
Sixty minutes with the decision-makers: the demo on your data, the score, the gaps, the fixed-price plan. You decide.
- 05Hand over, every time
Harness, runbook, training and the right to walk away are in every SOW. Retainers earn renewal; they do not hold you.
What our reports map to
Frameworks, not logos.
We map findings to the standards your risk, security and audit functions already use. We do not display those bodies' logos and we do not claim certification we do not hold.
How we chose what to build
Two reviews, one rule: deep-technical work on a pain a buyer is already paying to fix.
On 2 October 2026 we reviewed 152 sources on how AI agents are failing in production, and mapped 128 problems companies pay to solve across twelve areas — each scored on the money in it, the urgency, how much room is left and how fast a small team can make a first sale. No problem on the map is wide open; in 21 of them the largest seller is worth more than $10 billion. The open work is deep-technical service around existing products, for buyers the leaders ignore.
That is where the line-up sits: the service ladder on the joint-highest-scoring row of the 128, and five products on the rows where testing, cost, tool attestation and records are least served. What we said no to is on the record too — AI-built websites, a visibility monitor, another support agent, a generic red-teaming API, an identity platform — because the market data said someone funded already owns it or nobody is paying for it.
The six places still open and how we earn them are on the Lab page; the products and their public gates are on the products page.
Timeline
Where we are, and what is dated.
Dates in the past are facts the public record can check against our CIN and DPIIT number. Dates in the future are commitments; if one moves, the entry says so.
- 23 September 2026
Rainkernel Technologies Private Limited incorporated in Hyderabad, Telangana (CIN U62099TS2026PTC223231).
- 29 September 2026
Recognised as a startup by DPIIT under Startup India (DIPP285808).
- 30 September 2026
rainkernel.com launches with the Agent Production-Readiness Sprint and the free Readiness Score.
- 2 October 2026
Product line-up published after a 152-source review of enterprise AI pain in 2026: Gate, Governor, Support-Surge Reliability, MCPSentry, Compliance Evidence Pack.
- 18 October 2026 · planned
Readiness Kit v0.1 released as open source: agent attack pack mapped to OWASP ASI01–ASI10, evaluation harness, cost-per-task baseline.
- November 2026 · planned
Full Agent Readiness Gate ($25,000 / $45,000 tiers). Agent Cost Governor build starts.
- January 2027 · planned
Governor live in paying estates. Support-Surge Reliability pilots converting to run fees. MCPSentry build.
- Q1 2027 · planned
MCPSentry free scanner on GitHub; attestation early access.
- Q2 2027 · planned
Compliance Evidence Pack with design partners and the first accredited audit.
“I started Rainkernel after years of building AI systems inside large programmes and watching the same thing happen: the demo works, the pilot stalls, and nobody can say why. The reasons are always the same — no evaluation set, no cost number, guardrails described but never tested. Rainkernel exists to do that unglamorous part properly, inside your cloud, at a published price. If you have a use case, I'd like to hear it.”
Ravikumar leads engineering and every client readout personally. Rainkernel is founder-led and self-funded; we will raise outside capital only after paid engagements prove the line-up, and we say so because buyers ask.
Partners
Who we work through.
Much of what we build is sold inside someone else's engagement — a consultancy's programme, an auditor's request list, a vendor's renewal. We publish no partner logos until a partner asks us to.
Consultancies and systems integrators
You sold the AI programme; we provide the independent Evidence Report, the pods and the toolkit. White-label welcome.
Auditors and ISO/IEC 42001 consultancies
The Compliance Evidence Pack is designed with auditors, for auditors. Design partners shape the exports.
Agent vendors and platforms
Independent reliability and cost measurement on your customers' deployments — a renewal argument you cannot make about yourself.
Cloud and security partners
We deploy inside AWS, Azure and GCP estates and build on the open-source scanners and gateways the community maintains.
Company facts
For procurement and due diligence.
- Legal name
- Rainkernel Technologies Private Limited
- Incorporated
- 23 September 2026, Hyderabad, India
- CIN
- U62099TS2026PTC223231
- GSTIN
- 36AAQCR3546R1ZE
- Startup India (DPIIT)
- DIPP285808
- Registered office
- 12A04B, 13th Floor, Manjeera Trinity Corporate, Kukatpally, Hyderabad 500072
- Invoicing
- USD for international clients; INR with GST for Indian clients
- Working hours
- 09:00–21:00 IST, Monday to Friday — overlapping US East mornings and UK and EU afternoons
Registration documents, GST certificate, bank letter and the master services agreement template are available to prospective clients on request to hello@rainkernel.com. Security and data-handling details: Security and trust.
Tell us the use case. We'll tell you where it would stall.
A 30-minute call, no deck, no charge. You leave with an honest read on production readiness and, if it fits, a fixed-price proposal within 48 hours.