Austin, Texas, February 5, 2026. AI start-up, BigHammer.ai, launched today with a bold ambition: to disrupt the $500bn data and analytics market. BigHammer.ai’s team of AI Agents work together as a virtual data engineering function – redefining how data products are built, governed and run at scale.
As organizations struggle under the weight of fragmented data tools, siloed teams, and rising labor and platform costs, BigHammer.ai offers a fundamentally new operating model. Instead of assembling and maintaining complex stacks of legacy point solutions, BigHammer.ai’s team of AI agents automate data pipeline development, operations and governance end to end across the entire data lifecycle.
“Organizations want to drive value from data quickly, but they don’t want to buy multiple disparate tools to do so. Unfortunately, that has been the reality until now,” said Srinath Reddy B, Founder of BigHammer.ai. “We are set to disrupt this $500bn market with a team of AI agents that sit within data engineering teams enabling value to be created from data at a fraction of the time and cost.”
Built for modern data and analytics teams, BigHammer.ai replaces today’s disconnected tools and manual workflows with AI agents that can learn, plan, build, make decisions and act independently. The result is faster delivery, lower cost and dramatically reduced operational complexity – without sacrificing control, compliance or trust.
The AI agents are instructed and managed via natural language interfaces, enabling closer collaboration between business and technical teams – empowering citizen data engineers through self-service and reducing reliance on specialist engineering resources.
Unlike copilots that sit on top of existing tools and therefore only see part of the stack, BigHammer.ai is AI-native by design. Its agents securely ingest, catalog and govern data, build and operate complex pipelines, and deliver analytics-ready data and insights. As a result, organizations can:
- Scale data and AI without scaling headcount, cutting operational and labor costs by up to 70%.
- Deliver insights faster, removing engineering bottlenecks and empowering technical data engineers and citizen data engineers to build data products up to 70% faster.
- Radically simplify the data stack, accelerating legacy migration and rationalization while reducing total cost of ownership (TCO) by up to 30%.
- Automate governance and compliance, maintaining end-to-end data integrity, security and provenance across the entire lifecycle.
Founder Srinath Reddy B, formerly Head of Data Platforms & Engineering at Dun & Bradstreet and Head of Data at Aon, brings over 20+ years of frontline experience building and running large-scale data and analytical platforms.
“As a data engineering leader, I was constantly frustrated by disconnected legacy point solutions which all have their own dedicated software, infrastructure and specialist skills requirements,” Srinath continues. “BigHammer.ai is the product I always needed but never had. It’s born directly from the years of lived pain, stitching together disparate tools that didn’t scale and running huge data platforms under real operational pressure – not just designing them in theory.”
Four AI powered super agents, one coordinated approach
At the heart of BigHammer.ai are four specialized agents. Each agent has a defined persona, collaborates seamlessly with other agents, and is orchestrated by a meta-model that plans, coordinates and optimizes work across the data lifecycle – continuously improving as agents learn and share knowledge across deployments:
- Agent DataGov provides end-to-end data governance to inform and set guardrails for all agents while, delivering trust and transparency through metadata, lineage, quality and compliance.
- Agent Pipeline builds pipelines and accelerates modernization, using natural language to generate production-ready pipelines and support the migration of legacy data/code.
- Agent DataOps monitors and improves reliability across the data estate, including cost, latency and data quality signals. It reduces operational toil, accelerates the incident response, and finds opportunities to save costs.
- Agent Xplore helps teams explore and analyze data faster, enabling natural language-driven discovery, deep insights on data and next best action recommendations.
“We are excited about the launch of BigHammer.ai,” comments Sudhir Hasbe, President and Chief Product Officer at Neo4j. “Its agent-led approach will help our enterprise customers remove dependency on disparate tools and siloed execution in building knowledge graphs from various enterprise sources. BigHammer.ai is a meaningful step towards a more unified, automated future for data engineering. Srinath’s unique blend of pragmatism and deep data engineering expertise will help BigHammer.ai build a strong AI powered product offering!”
For more information, visit the website, or request a demo.
About BigHammer.ai
BigHammer.ai is an AI startup based in Austin, Texas, rethinking how data products are built and run. Its coordinated team of AI agents works as a virtual data engineering function to automate pipeline development, operations, and governance across the data lifecycle. BigHammer.ai helps organizations cut operational complexity and tooling sprawl while maintaining control, compliance, and trust. For more information, visit BigHammer.ai.
About Neo4j
Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. Trusted by 84 of the Fortune 100, Neo4j enables accurate, explainable, and governed AI through its enterprise-ready graph database and analytics capabilities across any environment or data source. Learn more at neo4j.com.