Smart Search & Selection for backlog triage
Describe what needs immediate attention ("Requests involving confidential information", "Requests over 90 days old") and pull them into a triage set. Sort before you read.
Backlogs aren't manpower problems.They're synthesis problems.
A source-grounded workspace for public-sector knowledge workers: clear records backlogs, audit policy consistency, defend every action with a citation.
No credit card. Audit-trail by architecture.
Public-sector work is reading and defending the read.
Public-records requests pile up. Policy consistency reviews take months. Every action has to be defensible: to the public, to oversight, to a court if it comes to that. The reading is unavoidable. The defending is what makes the reading slow.
The answer isn't faster reading. It's a workspace where every action arrives with the citation already attached.
Defensibility, built into the engine.
Every claim docAnalyzer makes is cited back to the source document and the source page. Every extracted field traces to where it came from. Every batch workflow produces an audit trail by default, not as an afterthought. The defensibility isn't a feature you turn on. It's the product.
Workflows public-sector teams ship
Built for defensible work.
Summarizer + Individual for consistency review
Run uniform summaries across a corpus, or ask the same question of every document in a policy review. Output is structured, cited, ready for review.
Data Extractor for records work
Pull standard fields from intake forms, applications, or filings into a structured table. Cited back to source for FOIA defensibility.
What public-sector leaders push on hardest.
Data residency requirements vary by jurisdiction.
Per-tenant isolation by architecture. Your team controls what's uploaded and where it lives. We don't pool data across customers, and we don't train on customer content.
Every action has to survive a FOIA-style audit.
Every cited claim is a clickable reference back to the source. Every extracted field traces back to the document and page. The audit trail is the citation system.
Public-sector procurement requires AI accountability standards.
Citations are built into the engine, not requested. Explicit context-adherence controls: dials that decide how strictly the model stays inside your sources. Multi-model fallback that doesn't sacrifice traceability. The accountability isn't optional. It's the engine.
Frequently Asked Questions
Can it help triage a records backlog?
Smart Search and Selection lets you describe what needs attention first, such as requests involving confidential material, and pulls that set out of the queue for you to work through.
How do I get consistent treatment across a large corpus?
Summarizer produces uniform digests across every document, and Individual asks the same question of each one and returns a per-document answer. Consistency comes from running one pass, not from remembering how you handled the last file.
Can I defend a decision afterwards?
Every cited claim opens the source at the exact page. When a decision is challenged months later, the record of what was read and where it came from is part of the answer rather than something to reconstruct.
Can standard fields be pulled from intake forms and filings?
Yes, that is the Data Extractor. It turns a folder of forms or applications into a structured table using the fields you define.
Where is the data processed, and can we constrain that?
Processing happens primarily in the United States. Enterprise plans can arrange data residency options and support SAML single sign-on so access is governed by your own identity provider. The security page has the detail.
Are our records used to train AI models?
Never, on any plan. Records are isolated per tenant, encrypted at rest with AES-256, and removed when you remove them.