Most companies fail at AI because the infrastructure doesn't exist. Off-the-shelf RAG breaks on real documents. Generic models can't handle regional languages. We built the missing layer.
Enterprises try to deploy AI and hit the same walls. We built infrastructure to break through them.
Complex PDFs, scanned contracts, multi-language forms. Standard OCR gives you garbage. Embedding-based search returns irrelevant results. You need 10 different tools and still can't trust the output.
Closed-source API models cost $20-30 per user per day at scale. Regional language support is an afterthought. Response times kill user experience. You need models trained for your specific use case, not one-size-fits-all solutions.
Banks, hospitals, legal firms—they can't send sensitive data to third-party APIs. They need on-premise. They need air-gapped. Most AI companies can't deliver that.
Three foundational systems that actually work in production
"We spent 18 months solving what everyone said was impossible."
"We don't sacrifice accuracy for speed. Or speed for accuracy."
"Banks can't use cloud APIs. We built for their reality."
Click any node to explore that layer
Every node represents infrastructure we built from scratch. Click to see what makes each layer production-grade.
We don't just use better tools. We build better systems.
Not a demo. Not a prototype. Production infrastructure serving real customers.
What happens when you deploy infrastructure that actually works
"We were processing 50K loan documents per day manually. Tried 3 different AI vendors—all failed on complex scanned documents. Dhanyog's system went live in 6 weeks. Now processing 200K documents daily with air-gapped deployment."
"HIPAA compliance killed every cloud solution. We needed on-premise with multi-language support. Dhanyog delivered both. Processing patient records in 12 regional languages, completely isolated from the internet."
"We were burning $15K/month on closed-source API calls. Response times were 2-3 seconds. Switched to Dhanyog's domain-trained model—same accuracy, 10x faster, 80% cost reduction."
We're working with select enterprises to deploy production AI systems. If you're processing documents at scale, need regional language support, or require on-premise deployment—let's talk.
Enterprise inquiries: enterprise@dhanyog.ai
Production-grade AI infrastructure tailored to your needs
Transform unstructured documents into structured, queryable intelligence. Our proprietary systems handle complex PDFs, scanned documents, and multi-language content with production-optimized performance.
Domain-trained models optimized for your specific tasks. We optimize at the token level for inference performance that makes a difference in production.
Your data stays yours. Deploy on your infrastructure—private cloud, on-premise, or air-gapped environments. Complete sovereignty with enterprise-grade reliability.
Whether you're processing millions of documents monthly or deploying models across global teams, our infrastructure scales with your needs. From Fortune 500 companies to high-growth startups, we deliver systems that work in production.
Foundational infrastructure built from first principles
We don't wrap existing tools. We build production systems from scratch, optimized for real-world constraints. Every component—from document processing to inference optimization—is designed for scale, accuracy, and deployment flexibility.
Our proprietary document understanding systems go beyond simple text extraction. We've built multi-layer processing pipelines that understand context, structure, and semantic meaning across complex document types.
Speed matters in production. Our token-level optimization techniques deliver 10x performance improvements while maintaining production-grade accuracy. We've built systems that understand the latency-accuracy tradeoff and optimize for real-world workloads.
Domain-trained models for 50+ regional languages, each optimized to hit the sweet spot between response time and quality that enterprises actually need.
Run anywhere. Our infrastructure supports private cloud, on-premise, and air-gapped deployments. Complete data sovereignty with the reliability enterprises demand.
Technical documentation for enterprise deployments
Our systems are designed for enterprise deployment. Contact our team for technical deep-dives, architecture reviews, and deployment planning sessions.
Dhanyog AI infrastructure consists of three core components:
We support multiple deployment models based on your security and operational requirements:
For detailed technical documentation, deployment guides, and architecture reviews, contact our enterprise team at enterprise@dhanyog.ai
Building foundational AI infrastructure that actually works in production
We build production-grade AI systems from the ground up. Not wrappers. Not thin layers over existing tools. Real infrastructure that solves real problems at enterprise scale.
Most AI companies take shortcuts—wrapping existing APIs, relying on generic models, and hoping for the best. We take the hard path: building custom infrastructure optimized for production constraints.
From document intelligence systems that actually understand complex PDFs to token-level inference optimization that balances speed and accuracy for real-world workloads. We don't just chase benchmarks—we solve the problems others consider too difficult.
Our systems process 100M+ documents monthly for Fortune 500 companies. They run in air-gapped environments for sensitive industries. They deliver low latency response times at scale.
This isn't research. It's production infrastructure that businesses depend on.
We're building the future of AI infrastructure. If you're a senior ML engineer who wants to work on hard problems with real impact, we're hiring.
Build production AI infrastructure that matters
Work on real infrastructure problems. No toy projects, no wrapper APIs, no shortcuts. Build systems that Fortune 500 companies depend on daily.
Build production document understanding systems that process millions of pages daily. Work on OCR optimization, layout detection, semantic parsing, and query infrastructure. You'll own critical systems that enterprise customers depend on.
Apply NowOptimize inference performance at the token level. Build training pipelines for domain-specific models. Work on regional language support and deployment infrastructure. Real systems engineering for production AI.
Apply NowOwn deployment infrastructure for private cloud, on-premise, and air-gapped environments. Work directly with enterprise customers on architecture, scaling, and operations. Build systems that deliver 99.99% uptime.
Apply NowWe're always looking for exceptional people. If you're excited about building production AI infrastructure, reach out at enterprise@dhanyog.ai