FNOL and customer communications
Provide voice, messaging, video, forms, queues, routing, callback, recording, transcription, and customer-status workflows.
Insurance
Private Insurance Claims, Underwriting & Risk Intelligence
Bring first notice of loss, voice and video communications, policy data, documents, photos, recorded evidence, computer vision, risk analysis, and human adjuster or underwriter review into one controlled private workflow.
OPTIME can combine Baasi communications with multimodal AI, document intelligence, computer vision, deterministic policy logic, private infrastructure, and review applications to reduce fragmented handoffs while preserving evidence and decision ownership.
WHY THIS MATTERS
Claims and underwriting depend on connected evidence-not isolated model output.
Insurance workflows frequently cross contact centers, policy systems, documents, customer photos, video, repair estimates, historical claims, adjusters, underwriters, investigators, and external partners.
A customer may repeat the same information across several channels while evidence is stored in separate systems.
- policy context;
- source evidence;
- image and video provenance;
- deterministic coverage and deductible logic;
- explanation;
- human decision authority;
- review and correction.
Connect claim communications, documents, photos, video, policy data, computer vision, deterministic rules, and adjuster review through one private evidence-backed workflow.
SYSTEM PRESSURES
Why simple implementations break down.
FNOL is fragmented
Voice, messaging, forms, photos, and policy information are collected through separate workflows.
Evidence is incomplete or inconsistent
Photos, video, statements, documents, and policy data may not align or may require additional evidence.
Damage review is slow
Adjusters spend time organizing media, identifying visible regions, and connecting findings with approved repair or replacement information.
Policy and evidence remain disconnected
A model may identify damage but cannot determine coverage, exclusions, deductibles, or payment authority by itself.
Underwriting information is document-heavy
Risk factors may be distributed across forms, inspections, images, documents, historical records, and third-party data.
Fraud and anomaly models can overstate certainty
Configured signals require investigation; they should not be presented as proof of fraud.
COMPLETE SOLUTION
Engineer the workflow as one controlled production system.
The complete system can connect Baasi contact center, voice, messaging, video, customer applications, FNOL, policy retrieval, document upload, photo and video upload, live remote inspection, STT, OCR, document extraction, computer vision, multimodal analysis, evidence correlation, deterministic rules, estimate assistance, risk-factor extraction, exception routing, adjuster and underwriter review, private infrastructure.
CAPABILITY GROUPS
What the complete Solution can contain.
Evidence intake
Accept photos, video, documents, live-session media, statements, device metadata, and approved third-party records.
Claims-document intelligence
Classify forms, extract structured fields, validate completeness, retrieve policy context, and link supporting records.
Photo and video analysis
Identify visible damage, affected areas, object or vehicle components, condition indicators, media quality, and additional evidence requirements.
Evidence timeline and consistency
Connect communications, documents, images, video, policy information, timestamps, and claim events into a reviewable evidence package.
Coverage, deductible, and rule integration
Use approved deterministic policy and calculation functions rather than asking a language model to invent coverage logic.
Estimate and reimbursement assistance
Combine visible evidence with supplied repair, replacement, price, or estimate data to prepare a recommendation for adjuster review.
Underwriting intelligence
Extract configured risk characteristics, compare them with approved rules, surface missing evidence, and route exceptions.
Anomaly and investigation signals
Surface unusual patterns or inconsistencies for authorized investigation without declaring fraud.
Human review and decision
Provide adjusters and underwriters with evidence, explanations, corrections, approval, rejection, and escalation controls.
ARCHITECTURE FLOW
Connect the complete path from source and session to operation.
The flow begins with customer, agent, adjuster, underwriter, investigator, and partner interactions and preserves control through every processing and operating layer.
Customer
Customer, agent, adjuster, underwriter, investigator, and partner interactions
Baasi voice
Baasi voice, messaging, video, recording, contact center, and routing
Forms
Forms, policy systems, documents, photos, video, and historical records
STT
STT, OCR, document extraction, CV, and multimodal analysis
Evidence timeline
Evidence timeline, provenance, quality, and consistency
Deterministic policy
Deterministic policy, deductible, calculation, and workflow rules
Draft estimate
Draft estimate, risk indicators, recommendation, and exceptions
Adjuster
Adjuster, underwriter, or investigator review
Approved claim or underwriting-system updates
Approved claim or underwriting-system updates
Monitoring
Monitoring, access controls, evaluation, and model lifecycle
ARCHITECTURE DECISIONS
Make important trade-offs explicit before they become operating constraints.
Customer upload or guided live inspection
Approach A
Customer upload
Approach B
guided live inspection
Selection considerations
Use asynchronous evidence when convenient and live video when an agent needs to guide capture.
Centralized CV or edge-assisted processing
Approach A
Centralized CV
Approach B
edge-assisted processing
Selection considerations
Process near capture where bandwidth, privacy, or immediate feedback matters.
AI estimate or deterministic calculation
Approach A
AI estimate
Approach B
deterministic calculation
Selection considerations
Use AI to organize visible evidence and deterministic functions for approved calculations.
Automatic action or adjuster review
Approach A
Automatic action
Approach B
adjuster review
Selection considerations
Keep material payment, coverage, fraud, and underwriting decisions under authorized control.
Public communications or private evidence platform
Approach A
Public communications
Approach B
private evidence platform
Selection considerations
Communications may use external connectivity while source evidence and analysis remain private.
REPRESENTATIVE SCENARIOS
How the Solution applies in representative situations.
Representative examples: Each workflow connects customer communication, policy context, multimodal evidence, configured rules, and an authorized decision maker.
FNOL call with evidence collection
- Scenario
- A customer reports a claim, receives a secure request for media, and the system organizes the communication, policy, and submitted evidence.
Live remote inspection
- Scenario
- An adjuster guides a customer through a video session while relevant frames and observations are preserved.
Vehicle-damage assistance
- Scenario
- Photos or walk-around video are processed into visible-damage indicators and linked to supplied repair or estimate data.
Property claim review
- Scenario
- Images, documents, statements, policy context, and prior records are assembled into one review package.
Underwriting evidence review
- Scenario
- Forms, documents, photos, and approved external records are analyzed against configured underwriting rules.
Investigation signal
- Scenario
- The system surfaces inconsistencies for an authorized investigator without declaring fraud.
ENGAGEMENT APPROACH
Move from operating context to a validated production system.
Phase 1
Claims and underwriting workflow assessment
Map communications, policy systems, evidence sources, decisions, rules, users, and private-data boundaries.
Phase 2
Representative evidence pilot
Prove one FNOL, remote-inspection, document, or damage-analysis workflow.
Phase 3
Platform implementation
Integrate Baasi, applications, policy data, evidence processing, AI, rules, review, and infrastructure.
Phase 4
Operational validation
Test media quality, exceptions, model behavior, calculation consistency, access, scale, and ownership.
POSSIBLE DELIVERABLES
Evidence and implementation that can transfer into operation.
Claims-intelligence architecture
FNOL and contact-center integration
Customer evidence application
Live inspection workflow
Claims-document pipeline
Photo and video analysis
Evidence timeline and review workspace
Policy-rule integration
Estimate-assistance workflow
Underwriting review application
Anomaly-signal workflow
Private model and media infrastructure
Final deliverables depend on the selected architecture, validation evidence, and engagement scope.
Start with the workflow, evidence, integration, deployment, performance, and operating constraints that determine whether this system can work in production.
START A TECHNICAL CONVERSATION
Discuss the system, constraints, and engineering outcome.
Share the product, workload, architecture, infrastructure, performance, security, or delivery constraint that must be resolved.
Austin, Texas
Distributed engineering teams across North America, Europe, the Caucasus, and Latin America.
[email protected]