Left Right Mind is an enterprise agentic AI platform that continuously compares your contracts, plans, and specs against your actual transactions, records, and reports. It finds the gaps, explains them, and closes them with evidence-backed workflows.
Documented intent
What your organization committed to
lives in contracts, policies, plans, specs, rate cards, and configurations.
Operational reality
What your organization actually did
lives in transactions, approvals, logs, records, and reports.
continuously surfaces gaps with traceable evidence.
closes each gap with human-in-the-loop workflows.
helps you understand those gaps
Continuously compare documented intent with operational reality to identify critical gaps. Every gap includes traceable evidence, supporting context, and a clear explanation of why it was raised.
Built for how your business defines a gap. It configures to your rules, thresholds, and definitions.
Something is conflicting in your intent.
Something is missing from the expectation.
Something has moved away from documented intent.
The patterns are comprehensive. The thresholds are bespoke.
Review, prioritize, and close gaps in this workspace. Every gap arrives with supporting evidence, a recommended action, and a configurable workflow, keeping your people in control of consequential decisions.
Built for how your teams already work. Resolve configures to your workflows, governance, and operating model rather than imposing a process of its own.
Bring reality back to intent.
Bring intent up to date with reality.
Record the rationale and close it as a justified exception.
The resolutions are comprehensive. The workflow is bespoke.
Interrogate every finding, ask why a gap was raised, which sources it came from, and what rule it broke. Explain answers in plain language, with the reference behind every answer. Work from a finding, a single source, or everything ingested for your use case.
Built for how your people already ask. Your documents, your data, your terminology.
The rule that was applied and the reasoning behind it.
Every claim traced back to the source it came from.
Related records, precedent, and patterns nearby.
The reasoning is comprehensive. The context is bespoke.
A growing body of research finds enterprise generative AI has yet to demonstrate widespread, durable value at scale.
Context becomes specificity. Silos become connected sources. Trust becomes evidentiary lineage.
Bespoke has historically meant months of build, hundreds of thousands in capital, and a 40–60% chance of never reaching production.
Detect, Resolve, and Explore are built, tested, and production-ready on day one. Your documents, your data, your workflows, and your rules are what get configured. Nothing about the platform waits on a build.
See Detect, Resolve, and Explore run against your own documents and records.
Request a walkthrough