Building the web context substrate for the autonomous era.
SchemaFlow was founded on a simple thesis: AI models are only as capable as the live context they can access. We eliminate the adversarial friction of web data collection so software teams can build world-class AI agents.
Powered by Amazon Web Services (AWS) Cloud
SchemaFlow’s high-throughput scraping, extraction, and brand intelligence pipeline is engineered directly atop AWS enterprise infrastructure, delivering sub-300ms global latency and automated elasticity:
Serverless Chromium Pods
Containerized headless browser clusters that auto-scale from 10 to 5,000 instances dynamically based on queue depth.
Multimodal Schema Engine
Vision-grounded schema extraction powered by Claude 3.5 Sonnet on AWS Bedrock for deterministic JSON generation.
Sub-Millisecond Cache
Amazon OpenSearch for vector retrieval and Amazon DynamoDB for global edge caching of 15M+ company brand records.
Private VPC Peering
Zero public egress for enterprise pipelines. Direct private endpoints via AWS Transit Gateway and VPC Peering.
The leadership behind SchemaFlow
Experienced engineers and systems builders pioneering web context intelligence for autonomous AI agents.
Tanish Bagul
Chief Executive Officer & Co-Founder
Technology executive and systems strategist directing SchemaFlow's enterprise growth, partnerships, and product vision. Passionate about building high-reliability infrastructure for agentic workflows and LLM web context.
Swetha Jain
Chief Technology Officer & Co-Founder
Distributed systems architect leading SchemaFlow's core engine, scalable Chromium scraping clusters on AWS ECS Fargate, and low-latency multimodal schema extraction pipelines.