Managed inference so you can find what's next
One governed interface routes every request to the model that does the job best, giving you frontier quality where it matters at a fraction of the cost, without complex configurations nor rules to manage.
Frontier-grade quality on complex tasks
Blended savings across typical workloads
Guaranteed availability
Every request logged, capped, and policy-checked
Frontier reasoning without the frontier bill
Prizmal routes each request into this zone, matching frontier quality at open weight cost
Reasoning scores from benchlm.ai (BenchAlign v5, July 2026), blended pricing from pricepertoken.com and provider rate cards
How it works
Three steps from your current stack to routed, governed inference
- 01Point to Prizmal
Swap your base URL and keep your existing SDK, prompts, and tools with nothing else to change
- 02We route each request
A lightweight classifier picks the smallest model that meets the quality bar for that specific call
- 03You keep the guardrails
Per team budgets, PII redaction, logs, and evals ship in the box so you stay governed by default
One control layer. Whoever owns the decision owns the layer. Across models and tiers, not within one. The bulk of your work stays on open models in your own environment; frontier is the escalation path, on your keys, only when earned.
Estimate your savings
A quick look at what routing through Prizmal could do for your workload
- Prizmal Seats + API Calls
- $6,625 / yr
- Prizmal Serverless Inference
- $25,000 / yr
Illustrative estimate, modeled as all-in seats plus $0.75 per 1,000 routed API calls (1 API call ≈ 150,000 tokens), serverless inference at $0.20 per million tokens at cost, against a frontier baseline at a blended $0.70 per million tokens, 250 working days per year. Rates are variable. Refine on your own traffic in the docs.
Point your app at api.prizmal.ai
One key, one policy, one stream you own