What we do
We run our own AI products and build AI systems for other teams. The work is the same discipline either way.
Products we operate and support.
Students and early-career engineers preparing for placements
A live voice interview of about 20 minutes built around your own CV, ending in a feedback report scored across five rubric dimensions.
School students and their parents (school learning, not a career product)
An AI Kannada teacher for school students whose mother tongue is not Kannada, built around the school syllabus.
Engineering capacity for building and operating AI features inside your product or organisation.
Voice agents, speech pipelines and structured feedback.
Extraction, generation and review pipelines.
Test suites and replay tooling for model behaviour.
When the problem is specific to your organisation: we scope it with you, build against agreed evaluation criteria, and hand over code, documentation and training.
A working version of the core workflow so you can judge it on real inputs. It is a prototype, not a production commitment.
Hardening, integration, monitoring and release, agreed as its own scope.
Four stages from first conversation to a team that can run the result. A scoped prototype is not the same commitment as a production delivery, and we say which one you are buying.
Map the workflow AI should own, who uses it, what data it touches and how success will be judged.
Agree the architecture against your existing systems, the evaluation plan and the scope of the first release.
A working prototype first, then evaluation against the agreed criteria, then production release. Each is scoped and agreed separately.
Handover of code and documentation, training for the people who will run it, and support on agreed terms.
