Turn document packets into decision-ready context.
Drop in an insurance document packet. Get a structured Context Pack, operational outputs, and an audit trail you can stand behind.
Built for insurance operations by a founder with 18 years in the field.
Product demo — Claims Intake & Document Intelligence
Product proof
See Adjustly in action.
A claim-native workspace that turns a messy packet into reviewable, evidence-linked outputs—built for intake, triage, and oversight.
- Document viewerPacket documents organized for fast review and retrieval.
- Extracted Tier-1 fieldsPolicy, loss, insured, and key amounts captured as structured values.
- Evidence linkageFields and summaries link back to supporting text spans.
- Apply-to-claim workflowReview, correct, and apply fields with clear checkpoints.
- Audit timelineVersioned runs and corrections preserved for QA and compliance.
Screenshot placeholder: replace with a real product screenshot when available.
The Problem
Insurance operations are still running on document packets.
Every file arrives as a bundle: loss notices, forms, estimates, photos, medical records, statements, emails, and vendor documents. The operational burden is predictable.
Manual re-keying into core systems and spreadsheets
Missing items discovered late, triggering rework loops
Inconsistent handling across adjusters and teams
Limited evidence linkage back to the original documents
Core platforms built for transactions, not document intelligence
Audit and QA that depends on screenshots and tribal knowledge
When the packet is the source of truth, you need a reliability layer that can prove what it used and what it produced.
A reliability layer between the document and the decision.
Adjustly ingests a document packet, classifies what's inside, extracts Tier-1 fields, and assembles a Context Pack that supports the next operational step. Every output is tied back to evidence spans so teams can review quickly and move with confidence.
What You Get
From packet to structured output.
Packet Ingestion
Matches real intake workflows. Documents in, structured evidence out.
Field Extraction
Structured field extraction designed specifically for claims operations.
Context Packs
Summarize what matters with evidence links. Facts separated from inference.
Explainability Views
See exactly what was used, what was inferred, and the confidence behind each output.
Versioned Runs
Correction history with full QA and oversight traceability.
Exportable Outputs
Push structured data to downstream systems and teams via APIs.
Product
Modular by design. Start with Claims.
Modules share the same evidence-first reliability layer.
Claims Core
A claim-native workspace for intake and triage with structured outputs generated from the packet.
- Who it's for
- Claims Ops leaders, intake teams, supervisors, QA, and adjusters who need consistency and throughput.
- Outcome
- Faster, cleaner handoffs from intake to handling, with fewer rework cycles caused by missing or unclear information.
Document Intelligence (v1)
Parses and classifies documents, extracts Tier-1 fields, and produces structured data with supporting evidence spans.
- Who it's for
- Teams handling high document volume who need reliable extraction without turning every file into a custom project.
- Outcome
- Less manual re-keying and fewer full-packet reads to understand basic file context.
Explainability & Audit
Evidence-first outputs: citations, fact vs inference, audit logs, and versioned run history with corrections.
- Who it's for
- Supervisors, compliance, audit, QA, and operations leaders who need defensible outputs and repeatable processes.
- Outcome
- Audit-ready operations without slowing down the frontline team.
Agent Workers
Automates bounded operational steps around intake and document handling, using the same evidence-first approach.
- Who it's for
- Ops teams looking to reduce repetitive coordination work while keeping humans in control of decisions.
- Outcome
- Higher throughput on routine tasks, with clear checkpoints and traceability.
Process
How Adjustly works in real operations.
A five-step flow designed for intake, triage, review, and oversight.
Ingest document packet
Upload or route a packet from your intake channel. Adjustly treats the packet as the system of record for evidence.
Parse and classify
Documents are identified and grouped so downstream steps are consistent, even when the packet is messy.
Extract Tier-1 fields
Key fields are extracted into structured outputs designed for claims workflows, with evidence linkage.
Build the Context Pack
Adjustly assembles a decision-ready summary and structured context, separating what is supported by evidence from what is inferred.
Review, audit, push downstream
Teams review quickly, corrections are tracked, runs are versioned, and outputs can be exported to downstream systems.
Short walkthrough
See the Context Pack and evidence linkage.
Lower-commitment than a full demo: get a sample output and a quick walkthrough of how packets become structured, reviewable fields.
- A sample Context Pack (summary + structured fields)
- How evidence spans support each key field
- What the audit timeline records during review and correction
We'll reply with a short walkthrough and a real sample output (no hype, no surprises).
Why Adjustly
Operational credibility, built into the product.
Evidence-first outputs and workflow-aware design so teams can move fast without losing control.
Evidence-first reliability
Outputs are tied to citations and audit logs so teams can validate quickly.
Insurance-native design
Built around claims workflows, not generic document tooling.
Operational realism
Designed for messy packets, exceptions, and oversight.
Fast onboarding
Start with document-drop onboarding and expand from there.
Founder domain depth
Built by someone with 18 years in insurance operations.
Outcomes
Outcomes that show up in daily operations.
Adjustly is designed to improve the metrics operations leaders actually manage.
Value depends on your packet mix, current workflows, and downstream integration needs.
Instead of re-keying policy number, loss date, and estimate totals across systems, teams review structured Tier-1 fields with linked source evidence.
Multi-document packets are classified into a consistent packet view (loss notice, estimates, photos, emails) so intake and triage steps stay repeatable.
Estimate totals and key amounts are captured as structured values with confidence and evidence—so low-confidence fields are easy to spot and verify.
Missing or inconsistent required fields are surfaced early—before the file is handed off—reducing back-and-forth cycles across teams.
Corrections are tracked as part of the record: versions are retained and the audit timeline shows what changed, who changed it, and why.
Enterprise
Enterprise-ready controls, designed for oversight.
Adjustly is designed for insurance operations: clear permissions, tenant-level isolation, traceable outputs, and controlled change.
Security posture
Data is hosted on Google Cloud (via Firebase). Connections are encrypted in transit (TLS), and data is encrypted at rest using Google Cloud default encryption.
Designed with SOC 2-aligned controls in mind. Program details available on request.
Data handling
- We do not use customer data to train models without explicit consent.
- Tenant data is isolated at the access-control layer (tenant-level rules and membership gating).
- Export controls are supported via role-based access and auditability around downstream pushes.
RBAC
Role-based access control for intake, adjusters, supervisors, and admins.
Tenant isolation
Tenant-level data isolation and membership-gated access across collections.
Immutable audit logs
Append-only audit timeline designed to be tamper-evident, with versioned outputs and correction history.
Versioned outputs
Runs are versioned so teams can review, compare, and trace changes over time.
Evidence linkage
Key outputs are tied to source evidence so reviews are faster and more defensible.
Core system positioning
Adjustly structures and validates document-driven inputs before data enters your core system. It does not replace your policy or claims platform.
Enterprise FAQ
Implementation questions CIOs and Ops leaders ask.
Clear answers about scope, integration, security posture, and what teams actually do day-to-day.
How long does implementation take?
Most teams start with a focused intake + review workflow. Timeline depends on packet sources and required fields, but an initial pilot is typically measured in weeks—not quarters—because onboarding starts with real documents and a bounded workflow.
Do you replace Guidewire or Duck Creek?
No. Adjustly structures and validates document-driven inputs before they enter your core system. Your policy and claims platforms remain the system of record.
How do you integrate?
Adjustly can export structured outputs (fields + supporting evidence references) to downstream systems and teams. Integration approach depends on where you want the data to land (queues, tasks, APIs, or files) and what validations are required before export.
Where is data hosted?
Data is hosted on Google Cloud via Firebase. Network traffic is encrypted in transit (TLS), and data is encrypted at rest using Google Cloud default encryption.
How is AI used?
AI is used to classify documents, extract Tier-1 fields, and assemble a Context Pack. Outputs are designed for review with confidence signals and evidence linkage so humans stay accountable for decisions.
Can we configure required fields?
Yes—required fields and review checkpoints can be aligned to your intake and triage workflow so missing items are caught before downstream handoffs.
How do audit exports work?
Outputs are versioned and the audit timeline records changes and corrections over time. Exports can include both the structured data and the context needed for QA (evidence references, timestamps, and run/version identifiers).
What does onboarding involve?
Onboarding starts with your real packet types and a controlled scope: define the initial workflow, validate required fields, and align roles (intake, adjuster, supervisor). Then expand coverage and export points once the review loop is stable.
Modernize insurance operations without replacing your core system.
If your process starts with a packet, you need outputs that are structured, reviewable, and audit-ready. Adjustly provides a reliability layer between the documents you receive and the decisions you make.