Request Early Access See Pricing
Early access — accepting qualified teams now

AI answers backed
by real evidence

Grounded retrieval and evidence for AI. Turn AI answers into source-backed outputs. DeepNova retrieves real evidence, structures it, and returns results tied to real sources instead of unsupported model guesses.

MCP Server + Developer API | Starting at $149/mo

What changes

Without DeepNova

× AI generates confident answers with nothing backing them up
× No way to trace where an answer came from or why it's wrong
× Retrieval dumps everything remotely related into the context

With DeepNova

Every answer tied to real, verifiable sources
Evidence traces you can audit and explain
Structured outputs your product can build on

What DeepNova does

Ground your AI in evidence, not guesses.

🔍

Grounded Retrieval

Retrieves real evidence relevant to the query — not just the closest vector match. Every result tied to a real source.

🔗

Evidence Traces

Every AI output comes with a trail back to the sources that informed it. Audit, verify, and explain any answer.

📜

Structured Outputs

Results come back as structured data your product can build on — not raw text blobs. Evidence graphs, execution traces, and telemetry.

Orchestration & Pipelines

Chain retrieval stages into pipelines with versioned steps. Each stage has typed inputs, outputs, and clear contracts.

🔌

MCP + Developer API

Use from ChatGPT, Claude, Cursor, and agent clients via MCP — or embed the API directly in your own product.

💰

One Platform, One Bill

Both MCP and API access included in every plan. No separate subscriptions, no surprise charges.

Better Together

DeepNova + NOVA Optimizer

DeepNova finds the 5 tools that matter. Optimizer consolidates them into 1 super-tool. 10,000 tokens become 300. 97%+ savings AND better accuracy. Save 20% when you bundle.

Simple, transparent pricing

Start small. Scale when you're ready.

Starter

For teams evaluating grounded retrieval
$149 /mo
  • MCP Server + Developer API
  • Grounded retrieval with evidence traces
  • Structured outputs
  • Email support
Get Started

Enterprise

For teams with custom requirements
$2,499 /mo
  • Everything in Pro
  • Unlimited usage
  • Dedicated infrastructure
  • SLA + dedicated support
  • On-premises deployment available
Contact Sales

Save 20% when you bundle with NOVA Optimizersee platform pricing

Frequently asked questions

What is grounded retrieval?
Instead of letting an LLM generate answers from its training data alone, grounded retrieval finds real evidence first, then gives the LLM that evidence to work with. The result is AI output tied to verifiable sources — not unsupported guesses.
How does DeepNova work with MCP clients?
DeepNova exposes its capabilities as MCP tools. Any MCP-compatible client — ChatGPT, Claude, Cursor, or your own agent — can call DeepNova to retrieve grounded evidence as part of its workflow. You also get a Developer API for direct integration.
Can I use DeepNova with the NOVA Optimizer?
Yes, and they're designed to work together. DeepNova retrieves only the relevant evidence, then Optimizer compresses it further. The combination delivers 97%+ token savings with better accuracy than either product alone. Bundle pricing saves you 20%.
What does "early access" mean?
DeepNova is accepting qualified teams now. Early access means you get direct access to the product and our team, help shape the roadmap, and get priority when new capabilities ship.
What do the structured outputs look like?
All outputs are structured JSON your product can build on directly. Results include evidence graphs, execution traces with per-stage telemetry, and source-backed data. No parsing unstructured text — everything comes back typed and ready to use.

Request early access

DeepNova is accepting qualified teams now. Tell us what you're building and we'll get you set up.

  • Direct access to the product and our team
  • Help shape the roadmap
  • Priority access to new capabilities
  • Bundle with NOVA Optimizer and save 20%
We'll respond within 24 hours. No spam, ever.