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AI-powered complaint management

Turn complaint text into decision-ready cases in seconds.

DataKnobs Complaint AI triages, summarizes, classifies, routes, and analyzes customer complaints across email, chat, forms, and call transcripts. It helps teams reduce backlogs, route cases consistently, uncover root causes, and maintain an audit-friendly record of why each case was prioritized and where it was sent.
30–60% Faster triage time
Fewer Misrouted tickets and queue ping-pong
Audit-ready Structured evidence and routing rationale
Trend-aware Theme clustering and escalation signals
Live workflow preview Complaint text → structured case
Ops + Compliance Ready

Complaint Summary

High Severity
AI Summary

Customer reports continued billing after cancellation, says support previously confirmed the issue was fixed, and requests an immediate refund plus written confirmation.

Category Billing Subscription / Continued Charges
Owner Billing Ops Auto-routed with confidence 0.92
Next Step Refund Flow Verify cancellation and confirm invoice history
Theme volume
Top complaint drivers
Routing queue
Next cases in review
Billing dispute with chargeback risk
Urgent
Product defect mentioned in return request
Review
Legal escalation language in email thread
Escalate
Evidence lines
“I canceled last month but I’m still being charged.”

“Support told me it was fixed and it happened again.”
How it works

Ingest, understand, route, and learn.

Complaint AI handles the full lifecycle from raw interaction to structured case, while preserving the evidence and analytics needed by operations, product, QA, and compliance teams.
01

Ingest & normalize

Connect email, CRM, ticketing, chat, forms, and call transcripts. Optionally deduplicate, detect language, stitch threads, and redact PII before analysis.

02

Understand the complaint

Use LLM summarization, complaint detection, multi-label categorization, entity extraction, sentiment, and escalation signals to convert narrative into structure.

03

Trigger workflow actions

Auto-route to the right queue, create tickets, suggest next-best actions, and send edge cases to human review when confidence is low.

04

Analyze & improve

Cluster similar complaints into themes, monitor top drivers, alert on anomalies, and use human feedback to continuously improve quality.

Capabilities

Purpose-built for triage, routing, evidence, and complaint intelligence.

The system is designed not just to detect complaints, but to make them operationally useful — with summaries, categories, highlighted evidence, ownership suggestions, and analytics that expose recurring patterns.
01

Complaint detection

Classify interactions as complaint vs not-a-complaint, with confidence scores and configurable reasoning for review workflows.

02

Evidence highlighting

Identify the exact lines or sentences that express dissatisfaction, billing disputes, broken promises, harm, or escalation language.

03

Complaint summaries

Produce concise and consistent summaries that capture what went wrong, what the customer wants, and what happened before.

04

Taxonomy classification

Map each complaint to category, subcategory, and root cause taxonomy such as Billing, Product Defect, Refund, Delivery, Fraud, or Compliance.

05

Entity extraction

Extract structured fields like product, order ID, subscription ID, dates, amounts, channel, location, and policy references into JSON.

06

Severity & routing

Score urgency, detect escalation conditions, and suggest the right owner, queue, priority, and next-best action for each case.

Complaint mining from calls and emails

Find complaints hidden inside long conversations.

Many interactions mix complaint content with general questions or account context. Complaint AI scans transcripts and messages to identify which interactions actually contain a complaint, then surfaces the evidence and meaning without requiring manual review of every line.

  • Works across phone calls, emails, chats, and tickets
  • Separates complaint statements from background context
  • Flags potential legal, safety, fraud, or discrimination language
Workflow automation

Reduce backlog without losing control.

Use configurable rules and confidence thresholds to decide when to auto-route, when to trigger SOPs, and when to escalate to a human reviewer for confirmation.

  • Auto-create tickets in the right queue
  • Trigger refund, replacement, or compliance workflows
  • Support human-in-the-loop review for low-confidence edge cases
Example outputs

Structured, explainable, and ready for downstream systems.

Instead of leaving complaints trapped in narrative text, the system produces outputs your teams and platforms can use immediately.
Structured output

Complaint case payload

Summary Customer reports recurring billing after cancellation and requests immediate refund.
Category Billing → Subscription → Cancellation / Continued Charges
Severity High
Suggested owner Billing Ops
Entities customer_id, subscription_id, dates, amounts
Recommended next step Verify cancellation timestamp, confirm last invoice, issue refund, send confirmation.
Trend intelligence

What leaders can see

Theme “Billing continues after cancellation”
Driver Volume spike in one subscription plan and one region
Risk signal Medium regulatory / charge dispute escalation risk
Operational action Route a sample to QA, trigger billing review, update dashboard and alert owner
Results & controls

Built to improve speed, consistency, and compliance confidence.

Complaint AI is designed for measurable operational value while preserving governance, transparency, and human oversight where needed.
30–60%Faster triage time with summary and routing automation
HigherFirst-contact resolution via next-best actions and templates
LowerMisrouting through consistent classification and rules
BetterProduct and CX insight from root-cause themes
StrongerAudit readiness with evidence trail and decision logs
Trust & security

Controls for regulated and high-volume environments.

  • PII redaction and role-based access control
  • Configurable taxonomy, business rules, and severity logic
  • Audit logs showing what was extracted and why it was routed
  • Human-in-the-loop review for low-confidence or high-risk cases
Where it fits best

Ideal for support, CX, product, QA, and compliance teams.

  • High-volume customer service and complaint operations
  • Regulated complaint handling in finance, healthcare, telecom, and marketplaces
  • Product teams needing visibility into recurring customer pain points
  • QA and risk teams sampling edge cases and escalations
Get started

See Complaint AI on your own complaint data.

We can run a fast pilot on a sample of complaints, calls, or emails and deliver a working triage and routing workflow, a business-aligned complaint taxonomy, top themes and escalation signals, and structured outputs ready for your downstream systems.