why primal
Find the evidence.
Understand the context.
Make the decision.
Why build with Primal?
Connect the sources, definitions, and rules that apply.
See supporting passages, conflicts, and unresolved interpretations.
Reuse Primal's engine and skills, with updates and technical support.
Where primal fits
observability & review
Inspect activity and outputs.
Find issues and investigate results.
Primal
Use the organization's chosen sources and rules.
Resolve meaning and apply relevant conditions.
Build in source traces and checks.
Agent frameworks & controls
Coordinate models, tools, and actions.
Enforce permissions and approval steps.
These roles overlap and complement each other. Primal works alongside your orchestration, security, and review tools.
See the development and runtime architecture →
The economics of checking
Checking and repairing AI output consumes professional time.
Correcting, rewriting, and verifying AI output
Read Workday's research →
Hanover Research surveyed 3,200 active AI users at organizations with US$100M+ revenue. Fieldwork: November 2025; publication: January 14, 2026. Rework includes more than verification.
Reconstructing, validating and defending AI output. Sage / IDC.
Read Sage's April announcement →
The Sage / IDC study covered 2,275 senior finance decision makers and influencers at companies with 20–1,999 employees; fieldwork: February 2026. Finance-specific findings. July research scope.
AI cleanup reported by respondents to Zapier’s survey.
Read Zapier's research →
Centiment surveyed 1,100 US AI users at companies with 250+ employees, November 13–14, 2025; published January 14, 2026. Cleanup includes more than factual checking.
Vendor-sponsored surveys; different populations and measures. These are industry findings, not Primal savings.
Evaluate professional work against your selected sources.

Expertise, applied.
Across your work.
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