Lightspeed Lab builds web applications, AI systems, and data platforms for teams that need to move fast without breaking things.
Engagements run end to end — discovery through post-launch support. Take one practice or combine them.
Fast, accessible, production-grade web apps and marketing sites built with modern frameworks.
Agents, assistants and chatbots that do real work inside your product — not demos.
Turning raw data into decisions — analysis, modeling, and reporting that hold up under scrutiny.
The plumbing underneath: pipelines, warehouses and schemas that stay correct as volume grows.
Automating the repetitive work — pipelines, workflows, and AI agents that run without you.
Took decades of handwritten paper ledgers to a full digital platform. A Gemini Vision OCR pipeline reads the old Tamil-handwritten pages — mixed scripts, numerals and inconsistent hands — and migrates them into structured records, voice replaces manual data entry, and collections, debts, and daily totals are tracked in real time.
For years we ran everything out of notebooks — collections, debts, daily totals, all handwritten in Tamil. Digitizing that felt impossible until I saw it actually reading our old ledgers and taking entries by voice. Now I get a clear picture of the business every single day instead of chasing numbers at month-end.
A conversational assistant built into an end-to-end school management ERP used by 50+ schools. Principals, teachers, parents and students ask questions in plain language — by text or voice, in Tamil, Telugu, Hindi, Kannada or English — and get a concise spoken or written answer instead of navigating modules, filters and reports.
The AI layer handles intent, tool selection and multilingual phrasing; the existing Laravel backend stays the system of record, so authentication, permissions and business rules govern every answer. Built for low latency on older Android devices and reusable by the mobile app.
Answers are scoped to the signed-in role — a parent sees their own child, a teacher their own class.
We dig into the problem, constraints, and goals before writing a line of code.
Architecture and scope are mapped out so there are no surprises mid-build.
Iterative development with regular check-ins, not a black box until launch day.
Deployed, documented, and supported after launch — not abandoned at handoff.
Speech in, speech out, and handwriting recognition for records that were never typed in the first place.
Tell us the problem and the constraints. We will come back with scope, architecture, and a timeline.