Features — LLM Cost & ROI Analytics

See what drives spend, quality, and engineering time—in one dashboard.

Supports OpenAI & Groq today • No prompt content stored (telemetry only)

Open the live demo See pricing
Sample charts: LLM cost trend, Prompt Health, Developer time saved
Sample data shown for illustration.

Built for Developers

See token drivers at a glance

Break down prompts vs outputs and spot bloat quickly. If you’re tuning parameters, our guide on temperature ranges helps you balance determinism and creativity.

Prompt Health you can act on

Indicators for over-generation and stability help you shorten responses and reduce retries—fewer do-overs, lower cost.

Faster iteration

Compare before/after prompts and see telemetry move. Open the live demo to explore with sample data.


Made for Tech Managers

Cost you can explain

Trends by model/task help you justify spend and decide where tuning gives the biggest ROI.

Time saved, not just tokens

See how fewer retries and tighter outputs translate into developer time saved. Use the in-page estimator from the demo to share a quick business view.

Capacity planning

Usage by hour and stability indicators help you plan peaks and avoid regressions after prompt changes.

Manager-focused dashboards: Track ROI and efficiency.

Value for the Organization

Privacy-first by design

We never store prompt or output content—only telemetry like token counts, timing, and high-level success signals. Learn more in Privacy.

Works with your keys

Connect OpenAI or Groq using your keys. If you’re evaluating more providers, you can still standardize on a single analytics view.

Start in minutes

Install via PyPI and open the dashboard with sample data to socialize outcomes before rollout. Check Pricing to pick a plan.

Cost & Usage Analytics

  • Cost over time, by model and task
  • Token drivers: prompt vs output
  • Parameter trends (e.g., temperature)
  • Usage by hour

Want to see these in action? Open the demo dashboard with sample data.

Cost & usage analytics sample chart

Prompt Health

  • Over-generation (bloat) indicators
  • Stability/consistency signals
  • Success & retry hints

For parameter guidance, check best temperature settings by task.

Prompt Health sample chart

Developer Time Saved

  • Time saved estimates from fewer retries
  • Before/after comparison views
  • Share a quick business snapshot

Prefer a quick estimate? Use the mini calculator in the demo. If your site has the ROI modal installed, launch it here.

Developer time saved sample chart

Integrations

OpenAI Groq Anthropic (soon) Azure OpenAI (soon) Vertex AI (soon) Bedrock (soon) Mistral (soon)

Support for additional providers will appear in-product as they’re ready.

Privacy & Security

Privacy: We never store your prompt or output content—only basic telemetry (token counts, timings, high-level success signals). This keeps analysis useful without exposing sensitive content. Read more in our Privacy Policy.

Security: See our Security page for contact and disclosure details.

How it works

  1. Install via PyPI
  2. Use your OpenAI or Groq keys
  3. Open the dashboard to view cost, health, and time saved
$ pip install docoreai
export DOCOREAI_KEY=YOUR_API_KEY
python -m docoreai start   # local agent & telemetry

Ready to explore with sample data? Open the live demo or jump to pricing.

FAQ

Do you store prompts or outputs?
No. DoCoreAI collects telemetry only (token counts, timings, success)—never your prompt or output content.
Which providers are supported today?
OpenAI and Groq today. Additional providers are on the roadmap and will appear in the product as they’re ready.
How accurate is “developer time saved”?
It’s an estimate based on fewer retries and shorter outputs. Use it directionally to show outcomes to stakeholders.
Can we deploy privately or on-prem?
Enterprise & Custom options can support private server/on-prem and priority response SLAs.
How fast can we start?
Minutes. Install via PyPI, connect a key, and open the dashboard to review sample charts the same day.