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The OS for HCP engagement

A regulated AI workforce, ready when you are

Step in as the role that matches your work. Each persona opens the slice of Lokatial built for them - switch any time from the avatar in the top right.

What Lokatial is, in plain terms

Lokatial is the AI operating system for HCP engagement in pharma and biotech. Instead of stitching together CRMs, content systems, and manual MLR queues, your field, medical, and compliance teams work alongside a regulated AI workforce that shares one explainable policy engine. Every agent action - a meeting plan, a scientific exchange, a draft response - is pre-cleared against EFPIA, the Sunshine Act, GDPR, HIPAA, and your own SOPs before it reaches an HCP.

The result: compliance moves from a bottleneck at the end to a guarantee at the start. Every decision carries citations, a rule trace, and a plain-language narrative - so any outcome is audit-ready the moment it happens.

Frequently asked questions

What is Lokatial?
Lokatial is the AI operating system for HCP engagement in pharma and biotech. A regulated AI workforce - Emsah for field, Relay for medical affairs and pharmacovigilance, and a shared policy engine for compliance - automates the engagement work that today is split across CRMs, content systems, and manual reviews.
What does a 'regulated AI workforce' mean?
Every agent action is pre-cleared against an explainable policy engine that encodes EFPIA, the Sunshine Act, GDPR, HIPAA, and your internal SOPs as executable rules. Each decision carries a full provenance trail - citations, the rule trace, and a plain-language narrative - so compliance and regulators can audit any outcome.
Which roles does Lokatial support?
Field representatives, medical science liaisons, medical affairs leads, and compliance officers each get a workspace tuned to their workflow. The same underlying agents and policy engine power all of them, so an engagement planned in the field carries the same audit trail compliance sees.
How does Lokatial enforce compliance?
Rules live in a versioned policy library written in Rego, tested in CI, and evaluated on every agent decision before it reaches an HCP. SOPs in Word or PDF can be translated into executable policy and routed to reviewers. Nothing ships to an HCP without a passing policy verdict.
Does Lokatial replace our CRM and content stack?
No. Lokatial's agents will register into your existing Veeva, Salesforce, SAP, Oracle, and IQVIA systems via A2A, MCP, and standard APIs - or run standalone on public data. Same agents, any stack.
Is Lokatial aligned with the EU AI Act?
Yes. Lokatial is designed to support the obligations the EU AI Act places on high-risk and limited-risk AI systems used in regulated engagement. The policy engine encodes risk management and data governance rules (Articles 9 and 10), every agent decision emits a plain-language rationale and citation trail for transparency to users and reviewers (Article 13), human-in-the-loop approvals are enforced before any HCP-facing action (Article 14), and immutable logs with model and policy version pinning support accuracy, robustness, and post-market monitoring (Articles 15 and 72). Lokatial supports customer conformity work; we do not claim independent conformity assessment.
How does Lokatial map to the NIST AI Risk Management Framework (AI RMF 1.0)?
Lokatial operationalises all four AI RMF functions. Govern and Map: a versioned Rego policy library plus SOP ingestion codify roles, risks, and context for each engagement type. Measure: every decision carries a policy verdict, source citations, and a rule trace, so risk and performance are observable per decision, not just in aggregate. Manage: human approvals, reviewer overrides, rollback of policy versions, and incident logging close the loop when a risk materialises. The same primitives support ISO/IEC 42001 AI management-system evidence.
What observability and transparency does Lokatial provide for AI decisions?
Every agent decision is fully observable. Lokatial captures a per-decision rule trace showing which policies fired and why, citation provenance back to the source documents, a plain-language narrative of the reasoning, the pinned model and policy version, any reviewer override, and an immutable audit-log entry. Decisions are replayable as bundles so compliance, medical, and external auditors can reconstruct any outcome without asking the team to remember it.