Secure AI Crown Bioscience Agentic Platform

Crown Agentic AI Platform: Building the Technical Foundation

We are building a unified, secure environment where AI works for Crown—protecting client data, elevating scientific rigor, and accelerating the work that matters most.

The sections below follow the same narrative we share internally: the tension everyone feels today, the problems we must solve, the platform we built, and the architecture that keeps it trustworthy.

01 One secure entry point replaces a sprawl of disconnected AI tools.
02 Agentic orchestration coordinates knowledge, analysis, compliance, and generation.
03 Every recommendation is cited, auditable, and aligned to Crown’s standards.

Platform Snapshot

  • AI everywhere today also means unmanaged risk everywhere.
  • Five systemic problems we refuse to normalize.
  • Unified platform with orchestrated agents layered for trust.
Outcomes Protect proprietary data, eliminate duplication, deliver consistent quality, retain full traceability, and give IT/QA one governed platform.
No Data Leakage Consistent Quality Complete Traceability Centralized Security

Why This Platform Matters

The Crown Agentic AI Platform answers a simple question: can we harness AI without compromising the way we work, the data we steward, or the quality we promise?

Everyone across Crown deserves clarity on what we are building and why. Scientists, commercial teams, IT, and quality see the same safeguards, the same governance, and the same payoff.

We begin with the tension people feel every day: AI tools are everywhere, yet the way we use them today often introduces as many risks as it solves problems. That tension is the starting point for this platform.

The Problem We Must Solve

Across Crown and throughout our industry we see the same five friction points. They slow us down, fragment our knowledge, and introduce avoidable risk.

Tool Sprawl

Teams bounce between public LLMs, niche utilities, and internal dashboards with no connective tissue. Every ask starts from scratch.

Data Leakage Risk

Sensitive client information leaves our control the moment it is pasted into an external chatbot. We cannot claw that data back.

Inconsistent Guidance

Different tools give different answers, none of which know Crown’s SOPs or historical decisions. We end up debating which AI to trust.

Lost Traceability

When clients or auditors ask “why,” we cannot reliably reconstruct prompts, tools, or data sources. Decisions become non-repeatable.

Invisible IT & QA Risk

Security and quality teams lack a system of record for AI-assisted work. No audit trail, no policy enforcement, no compliance proof.

Multiply those realities across hundreds of colleagues and dozens of workflows and the impact compounds: duplicated effort, contradictory outputs, and missed opportunities for excellence.

How the Platform Responds

Instead of humans stitching together five different tools, the platform gives every study director, analyst, or commercial lead a single, secure workspace. They ask one question and the platform orchestrates the work on their behalf.

Knowledge Agent

Searches our secured corpus—protocols, study readouts, publications—without letting a single byte leave the Crown firewall.

Analysis Agent

Surfaces comparable studies, highlights what worked, what failed, and what lessons are buried inside last week’s project notes.

Compliance Agent

Inspects SOPs and the latest regulatory updates, flagging anything that must be incorporated before a draft is created.

Generation Agent

Produces a protocol draft that blends Crown’s best practices, client-specific context, and up-to-date regulatory requirements.

Crown Journey

Strategic pillars and real workflows move together: each stage blends institutional knowledge, autonomous orchestration, and human judgment so outcomes stay fast, governed, and reusable.

Commercial Intelligence & Activation

Every pursuit starts with context-rich playbooks, live pricing logic, and the Commercial Strategist Agent aligning with sales systems.

  • Auto-assembles therapeutic data, historic case files, and negotiation guardrails.
  • Generates briefs, competitor heatmaps, and revenue scenarios from market signals.
  • Completes Salesforce hygiene, quote configuration, and profitability scoring.
  • Coordinates quotes, approvals, and MRS-AI scientific support in-line with policy.
  • Runs discount simulations and ROI models before proposals go out the door.

Study Execution & Protocol Excellence

The Protocol Composer Agent, Agent Force, and lab integrations convert signed scope into compliant, optimized execution.

  • Drafts protocols from quotes, client preferences, and analogous efficacy models.
  • Loops Study Directors for review while templating, versioning, and compliance checks run.
  • Builds SOP-aware task graphs that schedule facilities, resources, and telemetry feeds.
  • Surfaces anomalies from LIMS/ELN/IoT data and recommends mitigations in real time.
  • Produces interim reports and QA packets with drill-down traceability to raw data.
Explore Study Agent Scenarios

Client Service & Retention

The Client Relationship Companion keeps sponsors informed, delighted, and renewal-ready.

  • Automates surveys, sentiment analysis, and account health scoring across channels.
  • Packages deliverables, dashboards, and QA reports with contextual narratives.
  • Tracks retention milestones, renewal triggers, and targeted upsell offers.
  • Governs invoicing, knowledge retention, and late-stage regulatory responses.
  • Answers FDA/CFDA queries with auditable knowledge retrieval and policy-aware sharing.

Current Focus & Roadmap

We start where the impact is immediate, the risk is highest, and the value of institutional knowledge is greatest.

Current Focus

  • Business process transformation in Scientific Operations.
  • Protocol design, optimization, and data analysis workflows.
  • Full traceability and compliance baked into every recommendation.

What’s Next

  • Extend the same platform to commercial operations.
  • Integrate sales support, client communications, and market intelligence.
  • Maintain one security model, one quality bar, and one source of truth.

Agentic Architecture Diagram

Hover nodes to reveal responsibilities, click the Agent Orchestrator to inspect sub-agents, and select a sub-agent to highlight its end-to-end flow. Animated connectors make the orchestration tangible.

Crown Agentic AI Multi-layer Architecture USER EXPERIENCE LAYER AGENTIC AI LAYER DATA & KNOWLEDGE LAYER Sales & BD Workspace Prospect insights • Alerts Quote AI • Negotiation playbooks Client & Sponsor Portal Proposal reviews • Status feeds Secure collaboration • Alerts Study Director Console Protocol review • Escalations Monitoring • Decision support Operations Command Task queues • Capacity plans Telemetry • Alerting Client Success Desk Surveys • Health scores Retention playbooks Commercial Strategist AI Opportunity reasoning • Quote automation Market signals • Negotiation co-pilot Protocol Composer Quote-to-protocol reasoning Study Director collaboration Crown Agent Orchestrator LangChain-style task graph • Guardrails Memory • Tool routing • Governance Operations Conductor Resource orchestration Predictive monitoring Client Success Companion Experience orchestration Retention intelligence Knowledge Hub & RAG Fabric Vector + graph indexes • Policy gating Operational Systems Spine CRM • ERP • LIMS • ELN • QA systems Analytics & Compliance Vault Data lake • QA evidence • Dashboards AI Partner Mesh MRS-AI • Agent Force • Gen AI APIs

Layered Capabilities

Each layer combines agentic judgment, automated workflows, and governed data access so teams experience a seamless handoff from lead qualification through post-study retention.

User Experience Layer

Persona-aware workspaces surface alerts, decision prompts, and collaboration moments. Interfaces span web, CRM plug-ins, Teams/Slack copilots, and immersive dashboards.

Agentic Intelligence Layer

The orchestration graph decomposes objectives, selects specialized sub-agents, enforces policies, and learns from feedback. Human approvals lock critical junctures.

AI Service Mesh

Unified gateway integrates CrownBio models with third-party AI including MRS-AI, Study Report generators, computational pathology, and Agent Force for workforce automation.

RAG Knowledge Fabric

Retrieval pipelines join vector, graph, and tabular stores. Attribute-based access keeps studies compartmentalized while enabling cross-program learning under governance.