Turning Fragmented Data Into Grounded Intelligence.
Our journey began with a simple belief: enterprise data should accelerate decisions, not bury them. We specialise in transforming fragmented, siloed data into clear, actionable intelligence.
Trust is earned through accuracy. Every output from our platform is grounded in your verified data, not guesswork, so teams can act on it with confidence instead of second guessing what the numbers actually mean.
Entity Intelligence Platform for Enterprises
From messy data to structured knowledge graphs, we help teams connect the dots across systems, so every decision is backed by context, not guesswork. Our platform turns records into a living map of your business.
At GiKA, we didn't follow the crowd — we backed the data.
The core reason traditional database systems are inherently reliable and verifiable is that structure comes before data. On the contrary, modern Large Language Models possess no inherent data structure. Even when structured data was present, the training process flattened it. This architectural oversight is the precise root cause of the modern model context limitation and hallucination problem.
GiKA was founded by Dr. Manoj Agarwal to take on this problem from first principles. Manoj's career has been defined by architecting some of the largest, most sophisticated data intelligence networks in the world—serving as a Senior Staff Engineer at Uber AI (spearheading knowledge graph integration and semantic search for Uber Eats) and as a Principal Applied Scientist at Microsoft AI & Research, where he was the chief architect behind the web-scale Microsoft Product Knowledge Graph.
Combined with his early foundational work at IBM Research and a PhD focused on deep data mining, pattern recognition, and information retrieval, the technical blueprint for a more reliable, deterministic AI architecture was set.
Turning a paradigm-shifting idea into an enterprise-grade reality requires an exceptional collective. GiKA is built by a world-class team of engineers, scientists, and product builders who have spent their careers at the absolute frontier of technology and hyper-scale execution.
Our team draws its deep expertise from pioneering engineering organizations—including Microsoft, Uber, IBM Research, Rippling, and Razorpay to name a few—and brings together elite minds educated at the IITs, IIITs, UT Austin, and other leading national and global educational institutions.
While the rest of the industry is just waking up to the critical importance of Context Graphs, GiKA built the foundation years ahead of the curve. When we founded GiKA, the market believed brute-force LLM context windows would solve enterprise complexity. Years ago, the concept of a multi-layered, graph-based data framework for reliable AI systems sounded contrarian.
But, we knew otherwise.
Still today, understanding that you need a Context Graph is easy. Knowing how to actually build and scale at enterprise scale is a problem very few teams in the world can solve.
Today, GiKA stands as the world's most pioneering team in this space. We have engineered the industry's leading high-dimensional Context Graph topology over heterogeneous, multi-layered enterprise data silos—and we've done it in a massively distributed, scalable manner. Our tech maps the most complex, chaotic enterprise realities into a clean, deterministic operational matrix designed to handle the hardest enterprise tasks.
With this breakthrough architecture in hand, context is no longer a limiting factor.
We didn't just wrap an API. We are a team that has spent decades mastering the data architecture required to make enterprise AI reliable, that enterprises can trust with their data and with their most critical decisions.
Our Team