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 team behind SchemaFlow
Khushal Thakkar
Founder & Chief Executive Officer
Distributed cloud infrastructure engineer with deep expertise in scalable browser automation, web context indexing, and agentic workflows.
Maya Chen
VP of AI Systems & Extraction
Former frontier model evaluation lead specializing in multimodal document understanding, zero-selector parsing, and token optimization.
David Vance
Head of Infrastructure & Security
Ex-AWS Solutions Architect with a track record of architecting FedRAMP and SOC 2 Type II compliant VPC architectures for Fortune 500 SaaS.