Continuous Cognition.
10–100× Fewer Tokens.
Governor splits agent reasoning into zero-cost symbolic reflexes and high-value neural reflection. Agents that used to burn tokens on every observation now resolve most decisions in microseconds — at near-zero cost.
3 lifecycle tools
enable · status · disable
Reflex / Reflection
symbolic zero-cost + LLM high-value
5 credits/hour
full session billing + audit trail
Pairs naturally with Scheduler → for autonomous event-driven task scheduling
Free to start · No credit card required
Three Tools. One Cognition Lifecycle.
Enable, monitor, and end a Governor session. Each tool maps to a distinct phase of the agent's lifecycle.
Enable Continuous Cognition
Opens a Governor session for the current agent. Activates the Reflex/Reflection cycle, initializes the percept buffer, and begins passive knowledge enrichment from background tool results. One call replaces dozens of redundant LLM round-trips.
What it does
- Initializes symbolic reflex layer
- Activates percept buffer
- Starts passive enrichment loop
- Returns session_id for audit trail
What Teams Use Governor For
Any agent that repeats observations benefits immediately. The savings compound the longer it runs.
Slash LLM Costs on Repetitive Agents
Any agent that checks the same data repeatedly — inventory, pipeline health, lead counts — resolves most observations as zero-cost reflexes. The LLM only fires when something genuinely changes.
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Passive Data Enrichment
Governor accumulates facts from background tool results during idle cycles. By the time an LLM needs to reason, most answers are already in the symbolic store — fetched for free.
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Warden-Protected Percept Ingestion
Every percept Governor ingests passes through Warden automatically. Adversarial content from tool results never enters the symbolic fact space — no extra configuration needed.
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Long-Running ETL Jobs
Multi-hour jobs track progress as Logic facts. Governor's reflex layer monitors state transitions — only invoking the LLM for the final reasoning step. Token cost stays flat regardless of job duration.
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Constraint-Based Decision Routing
Business rules live in Logic as constraints. Governor reflexes match incoming percepts against those rules — escalating to LLM reflection only when no symbolic rule resolves the decision.
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Session-Level Audit Trails
Every tool call and cached result is automatically asserted as a fact during the session. Disable Governor and instantly replay everything the agent observed — zero extra logging infrastructure.
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Governor Gets Stronger With Other DataGrout Tools
Each integration sharpens the Reflex/Reflection cycle — from injection-safe percepts to change-aware scheduled tasks.
Symbolic Brain for Reflexes
Logic is Governor's symbolic brain. Every tool call automatically asserts facts into Logic's persistent store. Reflexes query Logic at near-zero cost — no LLM needed for pattern matching or threshold detection.
✦ Sub-ms reflex queries replace full LLM calls
Change-Aware Scheduled Tasks
Scheduler fires recurring or event-driven tasks; Governor tracks their outputs as Logic facts. Reflexes then detect when results change — avoiding redundant LLM calls between task executions.
✦ Zero LLM cost on no-change task cycles
Explore Scheduler →Injection-Safe Fact Space
Warden screens every percept that Governor ingests. Adversarial content from tool results never enters the symbolic fact space — protected at the ingestion boundary, not after.
✦ Adversarial content blocked before Logic assertion
Type-Safe Reflex Matching
Prism transforms raw tool outputs into SemIO-typed values before they're asserted into Logic. Governor reflexes then match on structured types — not brittle string patterns.
✦ Reliable reflexes on structured types, not strings
Skill Output Change Detection
Flow skills produce structured outputs that Governor asserts as facts. Reflexes detect when a skill's output changes between runs — skipping redundant LLM processing when results are stable.
✦ Skip LLM processing on stable skill outputs
Forged Skill Audit Trail
Forged Toolsmith skills are first-class tools for Governor. Their execution results are tracked as Logic facts automatically — making skill invocation history auditable without extra instrumentation.
✦ CTC-verified execution history, zero extra logging
Integrate Governor in Minutes
One import. Auth, retries, and error handling all handled by the Conduit SDK.
from datagrout.conduit import Client
async with Client(
"https://gateway.datagrout.ai/servers/{uuid}/mcp",
auth={"bearer": "your-access-token"}
) as client:
result = await client.perform("data-grout@1/governor.enable@1", {})
print(result["status"]) # "enabled"
print(result["session_id"]) # 42
print(result["billing_rate"]) # "5.0 credits/hour"
# Every subsequent tool call now auto-asserts facts into Governor's fact spaceAlso available in TypeScript, Rust, Elixir, and Ruby. View Conduit SDK →
Frequently Asked Questions
Everything developers ask before integrating Governor.
More questions? Read the full Governor documentation.
Agents that think smarter. Budgets that don't grow.
Governor is the only continuous cognition layer that splits symbolic reflexes from neural reflection — delivering 10–100× token reduction without changing a single line of agent logic.
Free to start · No credit card required