01 Position
AI software that reaches production, not just a demo
We design, build and deploy AI systems for businesses that need a working result — not a pilot that stalls. One accountable partner from the first conversation to the system running in production.
We also build developer infrastructure — Alpha K, engineering intelligence for AI coding agents.
02 The gap
Most AI work dies between the demo and production
Industry research puts the share of AI proofs of concept that never reach production between 70% and 90%. The model is rarely the problem. The gap is integration, data pipelines nobody owns, no monitoring, and no agreed measure of success.
That gap is the whole job, and it is what we build for from day one.
03 What we do
What we do
From a first prototype to intelligent systems running across the business — and conventional software when that is what the problem actually needs.
01
Custom software development
Web, mobile and internal applications built to your requirements — with or without AI, and delivered with AI-assisted engineering.
02
AI strategy & roadmapping
Find the highest-value opportunities in your business and turn them into a prioritised, costed plan.
03
Custom AI & ML development
Production-grade models and LLM integrations — designed, trained, deployed and monitored.
04
System integration & APIs
Connect platforms, tools and AI components into one coherent system. No silos, no manual handoffs.
05
Intelligent process automation
Remove manual steps and error-prone handoffs using rules, RPA and AI judgement together.
06
Cloud architecture & DevOps
Scalable infrastructure on AWS, Azure or GCP with pipelines that make releases routine.
07
Legacy modernisation
Move off ageing systems onto maintainable architecture — incrementally, without stopping the business.
04 How we build
We build with AI, not just for it
We use AI tooling inside our own engineering process — generating scaffolding and tests, automating the mechanical half of code review, keeping documentation current. It shortens delivery without loosening the standard, because every generated line is reviewed by the engineer accountable for it.
05 Alpha K
Built by RAVIM
Alpha K — persistent engineering intelligence for AI coding agents
Alpha K gives AI coding agents persistent, local understanding of software repositories through MCP — helping them find the right code, understand workspace context and perform controlled engineering operations without rediscovering the codebase on every task.
- Local-first
- MCP ready
- Persistent repository context
- Controlled engineering tools
“Analyse the current solution.”
One question, measured against Alpha K’s own codebase.
- 151,200tokens spent
- 21whole files pulled in
- 85%of it, just reading
And the next conversation repeats it. Alpha K keeps that understanding between sessions: above a 400-line threshold a whole-file read becomes an 80-line head plus a structural outline, and any narrower range still comes back byte-exact.
- WorkspacesRepositories as explicit workspaces, read-only or read/write.
- Code intelligenceCode graph, BM25 retrieval and cached workspace briefings.
- MCP & local-firstBounded tools over MCP. The repository stays on your machine.
06 Where to start
Not sure where you should start?
Answer five questions and get a real read on your situation — the first phase that makes sense for you, the risks your answers imply, and what to have ready before you talk to anyone. Free, no sign-up, and nothing leaves your browser.
07 What we think
What we think
We are new, so we have no client logos to show you. What we can show you is how we think about this work — at length, and in public.
01
What Makes an AI Proof of Concept Fail — and How to Avoid It
The statistics are sobering. According to industry research, anywhere between 70% and 90% of AI proof-of-concept projects never advance beyond the pilot stage to full…
02
LLM Integration for Business: A Practical Guide for Non-Technical Leaders
Large language models have moved from academic curiosity to business essential in a remarkably short time.
03
Legacy System Modernisation: When to Rebuild, When to Refactor, When to Replace
Every organisation of a certain age has them: legacy systems that are critical to daily operations but increasingly expensive to maintain, difficult to integrate with modern…
04
The Real Cost of Business Process Automation (And the ROI You Can Actually Expect)
Business process automation is one of the most reliably valuable investments a company can make.
05
Cloud Migration Done Right: 7 Mistakes Most Businesses Make
Cloud migration has become a strategic imperative for most businesses, but the journey from on-premises infrastructure to the cloud is rarely as smooth as the marketing…
06
How to Choose an AI Consulting Firm: 10 Questions to Ask Before You Sign
The AI consulting market is growing rapidly, and so is the difficulty of choosing the right partner.
08 How we work
How we work
Five steps, start to finish — structured enough to be predictable, flexible enough to absorb what we learn along the way.
01
Discovery & diagnosis
A deep-dive workshop into your goals, systems and real pain points. We ask the hard questions first so there are no surprises later.
02
Solution design
A blueprint covering technology choices, integration points, data flows and a milestone timeline you can hold us to.
03
Build & iterate
Short, feedback-driven sprints delivering working software incrementally — so you validate progress rather than wait for a reveal.
04
Deploy & integrate
Full deployment including testing, training and integration with your live systems, planned for a quiet cutover.
05
Optimise & support
After launch we monitor performance and keep improving. Support plans keep the investment returning value.
09 Start
Tell us what you are trying to build
A 30-minute call, no obligation. We will review your challenge, share relevant examples and tell you honestly whether we are the right fit.