Governed AI data access at scale
AI pilots work. Production scale is the real test.
The first 50 AI requests work fine. But at 500 per day, databases slow down. At 5,000, costs become unpredictable. dhino is built for production-scale AI from day one.
What happens after the pilot succeeds?
Most AI data access patterns were designed for demos, not production. Each request runs expensive AI inference even for questions with known, deterministic answers. At scale, this means unnecessary load on both AI models and databases, unpredictable costs, and governance controls that break under volume.
"Less than 50% of AI systems achieve acceptable accuracy on structured enterprise data queries."
The scale challenge
Pilot-stage AI access patterns break in production. Every enterprise hits this wall.
Without dhino
- ✕ Database overload at high request volume
- ✕ Unpredictable AI inference costs
- ✕ No visibility into what AI is querying
- ✕ Governance degrades as volume grows
With dhino Trust
- ✓ Optimized execution via deterministic templates
- ✓ Predictable costs with template-based routing
- ✓ Full audit trails on every AI request
- ✓ Governance scales automatically with volume
How it works
Production-grade AI data access without the production-grade headaches.
Templates replace inference
Structured data queries are routed to deterministic templates instead of expensive AI inference. Fewer tokens, faster answers, lower cost per request.
Guardrails prevent overload
Access controls, query optimization, and caching are built into the platform. Your databases stay healthy even at thousands of requests per day.
Governance scales automatically
Every request goes through the same controls regardless of volume. Role-based access, audit trails, and policy enforcement work the same at 50 requests or 5,000.
What changes for your platform
Predictable AI operating costs
Template-based routing means structured data queries bypass expensive AI inference. Costs scale linearly with usage, not exponentially with complexity.
Databases stay healthy under load
Built-in caching and query optimization prevent AI from overwhelming your data infrastructure. Performance stays stable as request volume grows.
Governance that works at volume
Access controls and audit trails are part of every request, not bolted on after the fact. Compliance stays intact whether you process 50 or 50,000 AI requests per day.
Scaling AI is one of several challenges dhino solves for enterprise data access. Explore dhino Trust
Ready to scale AI with confidence?
See how dhino gives your AI platform governed, production-grade data access that performs at any scale.