We manage inference so you can find what's next
One interface for every agent token stream, delivering frontier-level reasoning at a fraction of the cost without complex setup or management.
Live from the calculator below. Run your own numbers
Routing layer target, custom SLA terms on Enterprise agreements
Every request logged, capped, and policy-checked
Frontier Reasoning scored on BenchAlign v5, July 2026, via benchlm.ai. Cost modeled in the calculator below. The outlined chip marks a commitment. Plain numbers are measurements.
Beyond Intelligent Routing
Serverless managed inference for coding agents. The control layer keeps deciding while the answer is written: open models carry the routine spans; frontier steps in only when the span requires it. When a better model ships, it is tested, benchmarked, and the mixture updates transparently.
Mid-trajectory escalation changes the control boundary. The frontier model is used sparsely, only for the spans that require it. Most of the workload stays on open models.
Every handoff carries the full context. The next model picks up mid-thought and your agent never notices.
Allowlists, spend caps, kill switch, full audit trail. Policies apply before and during streams.
Copilot
Cursor
Windsurf
Claude Code
Cline
Codex
opencode
Pi
Aider
OpenAI
Anthropic
DeepSeek
Qwen
Kimi
GLM
Frontier reasoning without the frontier bill
Your coding workloads execute within the Prizmal zone, achieving the optimal balance of reasoning depth and cost efficiency
Higher scores exist. They price at 12x to 22x the Prizmal position. benchlm.ai and pricepertoken.com, July 2026.
Estimate your savings
A quick look at what Prizmal managed inference could do for your workload
Agents passed humans in token usage this year, and global inference now clears 300 trillion tokens a day. The mix is the new cost line.
Parallel agents per seat, the default
For scale: a workday assistant seat runs about 6M tokens a day, a full-day coding agent about 20M, and parallel-agent seats pass 60M. Profiles from published 2026 agent token math and provider usage data.
- Frontier baseline
- $577,500
- Prizmal total
- $186,525
- Seats ($29 list)
- $17,400
- Routing ($0.75 / 1k calls)
- $4,125
- Serverless inference ($0.2/M)
- $165,000
Seats at the $29 Team list price. Pricing.
Estimate on list pricing: seats at the $29 Team list (Enterprise volume pricing at 10+ seats is custom, so list is the conservative ceiling), plus $0.75 per 1,000 routed API calls (1 call ≈ 150,000 tokens), serverless at $0.20/M at cost, frontier baseline at a blended $0.70/M, 250 working days.
Governance
The layer that inspects is the layer that records. Where tokens went, what agents were allowed to touch, and what was refused: one exportable trail.
| Gate | Volume | Checks | Refused | Escalated |
|---|---|---|---|---|
| TOOLS | 18,420 | 214 | 61 | |
| MCP | 9,106 | 88 | 24 | |
| CI/CD | 3,742 | 47 | 12 | |
| SPEND | 12,980 | 9 | 3 | |
| REGION | 44,311 | 0 | 0 |
Same fields in the export: JSON, CSV, or streamed to your SIEM
What the board asks
Ungoverned agents are a CFO and board nightmare: unbounded spend, answers no one can audit, public code bleeding into proprietary repositories. The panels above are technical. The reason for them is not.
Per-key, per-team, per-agent caps with a mid-answer kill switch. The bill cannot outrun the budget by more than one answer.
Every refusal, escalation, and approval in one trail, scoped to a window, filterable by team, key, and agent. Evidence on demand.
Public code entering proprietary code is a diligence failure waiting for an acquirer. Allowlisted models only, CI/CD gates on agent-written changes, and the per-span record shows which model wrote what.
SOC 2 Type II examination in progress. EU AI Act and ISO 42001 posture, region and residency enforced at the routing layer. One export answers the auditor, the underwriter, and the audit committee.
Insurers underwrite what they can see. Boards approve what they can defend. Your auditor gets the export instead of a meeting.
See where every token went: which model wrote which span, at what cost, under which policy.
Every routing decision and every control-plane change, logged and exportable.
Allowlists and blocklists for the tools and MCP servers your agents may touch. Grey areas escalate to a human.
Agent-written changes meet policy before they merge. The pipeline enforces what the meeting decided.
Per-key, per-team, per-agent caps. A kill switch that works mid-answer.
Region and residency enforced at the routing layer. EU AI Act and ISO 42001 posture, SOC 2 in progress.
When the board asks what your agents did last quarter, this layer is the answer: a complete record of every decision an agent was allowed to make, and every one it was not. Insurers underwrite what they can see. Boards approve what they can defend. Directors and officers get the file their duty of care asks for, and your auditor gets an export instead of a meeting.
How it works
Three steps from your current stack to managed inference
- 01Get an API key
Create your account and generate a key in a couple of minutes
- 02Point to Prizmal
Set one base URL in your coding harness and keep your existing agent, prompts, and tools
- 03We manage each request
We handle execution for every token so you can find, plan, build, and scale what's next
1# ~/.zshrc or ~/.bashrc2export ANTHROPIC_BASE_URL=https://api.prizmal.ai/anthropic3export ANTHROPIC_AUTH_TOKEN=$PRIZMAL_API_KEY4export ANTHROPIC_MODEL=prizmal-autoWorks with the coding harnesses you already run, no rules to define and no agent to rebuild
Sixty seconds, start to routed
One key, one base URL, first routed request. See the full developer setup →
Point your app at api.prizmal.ai
One key, one policy, one stream you own
No self-serve signup yet. We onboard you by hand and you have your key the same day.
In production with a limited group of teams since July 2026.
Your code passes through the layer. Zero retention, never trained on. How we handle data