Gyanvex designs and builds AI software, tools, and custom AI solutions — from small automation projects to full applications — for businesses and institutions that need something practical, not just a demo.
Gyanvex ("gyan" — knowledge, applied at the vertex of data and decision) is an AI software company. We build AI-powered tools, applications, and custom AI solutions for businesses and institutions.
We work closely with technical and non-technical stakeholders to turn a real problem — too much manual work, messy data, slow processes — into simple software that people actually use.
Every project we ship is built to be understood by the people who rely on it: what it does, how it decides, and why.
Models are evaluated against real-world edge cases before deployment, not just benchmark accuracy.
Every output traces back to its evidence — no black-box conclusions.
Role-based access, audit trails, and on-premise or private-cloud deployment options.
AI software and solutions that can be built standalone or combined into a single project.
Ingest, clean, and structure large volumes of unstructured data from documents, logs, and open sources into searchable, analysable form.
Entity extraction, classification, and summarisation across English and Indian languages, tuned for domain-specific terminology.
Flag irregularities, duplicate records, and suspicious patterns across large datasets faster than manual review.
Interfaces that surface the evidence behind a recommendation, built for analysts and case officers, not data scientists.
Image and document analysis, redaction, verification, and classification pipelines.
On-premise, air-gapped, or private-cloud deployment with full access control and audit logging.
Two small tools built to demonstrate how we approach applied, everyday AI problems.
A lightweight web tool that converts Word, images, and scanned pages into clean, searchable PDFs — and back again.
Paste in a long report, notice, or case file and get a clean, structured summary with the key points pulled out.
We start with the operational reality — the data you have, the decision being made, and what "correct" looks like.
A working proof-of-concept on real (or representative) data, so value is visible before commitment.
Production deployment matched to your infrastructure and compliance requirements.
Ongoing monitoring, retraining, and feature development as the use case evolves.
Whether it's an early conversation or a specific project brief, we'd like to hear about the problem you're solving.