The sovereign, model-agnostic workspace where insurers, MGAs and brokers learn, collaborate, share and get work done. Put today's best AI models to work across your firm's knowledge—without giving up control of your data.
Your teams, models and knowledge pods in one place.
Large property losses increased in the coastal segment versus the prior quarter. The shift is concentrated in three accounts, with weather-related claims contributing most of the change. Review the underlying claims and exposure notes before adjusting the portfolio view.
Compare by occupancy and geography →
Draft the monthly portfolio brief →
Reasoning gets sharper. Context windows grow. New specialists arrive. Don't marry your insurance operation to a single model: keep your firm's knowledge in one governed home and let the models change around it.
PolicyDock routes each request to a suitable model under your governance and cost rules. Ask a complex coverage question, analyze a long claims file, read a scanned loss run or classify a batch of submissions—each job gets an appropriate path.
Three accounts account for most of the change. The answer links the Q2 loss run with the portfolio exposure notes.
Saved prompt and cited answer, available to the claims reviewers with access to this pod.
AI work shouldn't disappear into individual chat histories. Memory follows each user and each knowledge pod. A firm feed surfaces questions, cited answers and useful prompts so the next team can build on what has already been asked.
A private workspace is only useful when the knowledge inside it moves. Organize it, interrogate it, watch it change and put it to work—without losing the permissions or evidence behind it.
Build focused pods around a portfolio, account, line of business or claim. Each pod holds its own sources, conversations and memory, with independent permissions. Query across pods when your role allows and follow citations back to the underlying evidence.
Extract structure from unstructured files, shape it into tables and build live charts from the results. Drag knowledge pods onto a canvas to compose a dashboard, then tailor what each viewer sees according to their access.
Define conditions against your data and let signals surface the moment those conditions are met. Keep watch on the movements that matter while your team is busy with the next submission, renewal or claim.
Latest loss-run data meets the condition. Open the cited source and compare against exposure changes.
Run queries on a schedule or trigger them when new data arrives. Chain steps into a governed workflow, then deliver a report or alert with an audit trail of what ran, what it used and who received it.
Import documents directly, or use API and MCP pathways to connect PolicyDock with the tools and data flows your organization already uses. These open extension points make room for the sources and workflows specific to your environment.
Bring context into one governed workspace
A folder of messy scans shouldn't mean a week of manual re-entry. Smart OCR reads batches of loss runs and claim documents, extracts structured fields and places the results in a cited knowledge pod.
Claim no. 00418
Date of loss 04 / 17
Cause Wind / water
Paid $84,320
Reserve $26,500
Scanned documents and extracted records, organized for questions, tables and downstream workflows.
↗ Open source page 3Process in batchesMove beyond one document at a time when the inbox fills up.
Preserve provenanceEvery extracted field stays connected to its source scan.
Make it operationalUse structured results in pods, dashboards and automations.
A forthcoming suite will orchestrate models and reusable templates around your company's knowledge to produce the work that follows the analysis: presentations, spreadsheets, reports and collateral. Start from a trusted pod, not a blank page.
Insurance knowledge carries sensitive customer, commercial and operational detail. Keep AI useful without moving that knowledge into public-model workflows.
Keep proprietary submissions, claims data and internal analysis out of public AI services. Model access runs within your private AI environment.
Run in a managed private cloud or an on-prem environment aligned with your infrastructure and data-residency needs.
Pod and user boundaries govern who sees what; activity and automated work retain a reviewable audit trail.
Different insurers have different requirements for control, operations and residency. Choose the deployment model that fits your environment.
Want to get specific about your documents or deployment needs? Let's talk.
Ask us directlyThe harness routes a task according to its needs and your governance and cost rules. Users can override the model for an individual query; private and on-prem models can be included in the available choices.
Your firm's context lives in PolicyDock rather than in one model's chat history. New models can join the harness without requiring your teams to rebuild their knowledge pods.
No. Pods have independent access controls, with Admin, Editor and Viewer roles. The firm feed and cross-pod questions respect those boundaries.
Import working documents including PDFs, scanned files and spreadsheets. API and MCP pathways also support controlled connections to other workplace data flows.
Yes. Automated BI turns permitted pod data into tables and charts, with dashboard views shaped by each viewer's access.
PolicyDock is designed around private models, dedicated deployment, pod and user isolation, governed sharing and auditability.
Choose a managed private cloud environment or an on-prem deployment under your organization's roof. We can discuss the infrastructure and operating requirements that matter to your team.
See how PolicyDock brings insurance knowledge, people and AI together.
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