AI agents that spend less and do more.
Exemplar governs AI agents running in your SDLC — cutting token waste, enforcing access policies, and making every run deterministic and audit-ready.
token_spend.week
$0
calls.blocked.today
0
model_routing.savings
0%
audit_trail.completeness
100%
The problem
Your agents are running in production.
Nobody knows what they're spending.
No budget limits. No access controls. No audit trail. Most teams discover the problem after it becomes an incident.
3.2×
average token overspend when agents run without model routing or budget enforcement
74%
of agent failures traced to unrestricted tool access — agents calling APIs they should never reach
0
audit records kept by most teams — no log of what ran, what it touched, or who approved it
Before vs. after
The same agent. Two very different outcomes.
One runs ungoverned — expensive, unrestricted, unaccountable. The other runs through Exemplar.
Without Exemplar
With Exemplar
The numbers
What governed agents actually look like.
Data from engineering teams running AI agents through Exemplar — before and after governance was enabled.
Weekly token spend
before vs. after Exemplar
Model routing distribution
tasks auto-matched to right model
Blocked calls by category
last 30 days across all agents
Agent run outcomes — daily
passed / approved / blocked
How it works
Every agent call passes through
the same policy gate.
Whether the agent runs from Cursor, Claude Code, or a CI/CD hook — the rules are identical.
01 — trigger
Agent makes a call
Agent on LangGraph, ADK, or CrewAI requests a tool, API, or service action.
→02 — intercept
Exemplar intercepts
The call hits Exemplar's policy engine before reaching your infrastructure. Zero code changes.
→03 — evaluate
Policy evaluated
Budget check. Tool allowlist. Approval gate. Model routing by complexity.
→04 — decide
Allow, block, escalate
Executed, blocked silently, or held for human approval — in milliseconds.
→05 — record
Logged and auditable
Requester, action, decision, timestamp — immutable record of every run.
Guardrails
Define exactly what your agents
can and cannot touch.
Set access policies once. Every agent — on every framework — operates within them.
Tool access control
agent-code-review · last run 4m ago
Cost governance
budget tracking · all agents · this week
The autonomous agent era is here.
Run it with a harness.
The teams governing their agents today will outpace everyone else. Exemplar is the operating layer they'll run on.
Blog
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