New Delhi India,Dec 9:- Faced with a steep increase in online child exploitation in India, law enforcement agencies are turning to advanced AI-driven tools to accelerate investigations and deliver justice. According to the National Centre for Missing and Exploited Children (NCMEC) agencies in India received 2.2 million cybertips related to abuse in 2024.

Playing a pivotal role in tackling this problem is Katalyst, an AI-driven digital investigation platform developed by Kindred Tech, a nonprofit organization that builds cutting-edge tools for law enforcement and NGOs to combat online child exploitation, human trafficking, and other technology-enabled abuse.

For law enforcement officers, manual processing of cybertip reports is slow and resource-intensive. Each report contains an average of 35 pages of information, and while much of it may not be directly relevant, a single piece of hidden data can provide a crucial lead for investigators.

Katalyst’s primary function is to automate the ingestion and prioritization of cybertipshelping to save authorities time, create resource efficiencies, and leading to a range of better outcomes which could include the identification of a victim, stronger evidence packages for a court case, or removing someone from a harmful situation.

Katalyst empowers law enforcement with four essential capabilities:

These features streamline investigations, surface actionable insights, and enable agencies to process large volumes of digital evidence efficiently. Katalyst also enables investigators to automate case workflows—bridging technology gaps and encouraging a more coordinated, cross-jurisdictional response.

At the core of Katalyst is MongoDB Atlas’s AI-ready data infrastructure, which scales effortlessly to meet the demands of modern environments, using both structured and unstructured data. MongoDB also underpins every AI function in Katalyst, empowering Kindred Tech to store AI inferences alongside raw case data, to run vector-based similarity lookups for victim IDs, and to train, tune and deploy models more efficiently. These capabilities are important for Katalyst to quickly deliver coordinated responses to combat online child exploitation.

In India, the platform’s impact is already evident. In 2024, Kerala Police’s Counter Child Sexual Exploitation Centre (CCSE) started an 18 month pilot project with Katalyst. During that period investigators relied on Katalyst to make notable improvements in the volume of cases they were able to resolve, which included making 96 arrests, safeguarding 20 children, and issuing 18 international referrals. The initiative was recognized with the Technology Sabha Excellence Award 2023 for its innovative use of technology in protecting children.

“At Kindred Tech, our mission is to empower investigators and law enforcement agencies with tools that surface insights faster and ensure every child’s case receives the urgent attention it requires,” said Bree Atkinson, CEO at Kindred Tech. “MongoDB helps us combine the existing data with the power of AI so Katalyst can surface critical insights faster, allowing Indian investigators to spend less time buried in data and more time safeguarding children.”

MongoDB’s offline-ready features allow Katalyst to remain effective even in low-connectivity, resource-constrained environments, empowering investigators to act decisively in challenging conditions. This capability makes it field-ready for law enforcement across India and beyond.

“The efforts to safeguard children are a race against time. Yet legacy systems and siloed data often create critical delays,” said Sachin Chawla, MongoDB VP India and ASEAN. “We’re so proud of how Kindred Tech is combining the outstanding field work of law enforcement with modern data platforms and AI to turn massive volumes of digital evidence into immediate, life-saving insights.”

Looking ahead, Kindred Tech plans to expand Katalyst across at least three additional Indian states over the next year. They also intend to enhance Katalyst’s capabilities with MongoDB Atlas Vector Search for image matching. This will enable cross-border investigations in real-time, and harness predictive analytics to transform investigative responses at scale.