Support OS for ops leads

Stop guessing why AI gets
your replies wrong.

Built for ops leads who've tried every AI reply tool and still end up rewriting everything. Work Hat tells you why.

Every edit your team makes is classified automatically
AI reads the full customer + company context before drafting
Dashboard shows exactly where the AI is failing — and why

No credit card. No noise. We review every request.

How it works

The full loop — from email to insight

Work Hat doesn't just draft replies. It captures what your team changes, classifies why, and builds a measurable record of AI quality over time.

3 new
billinghigh risk

Every inbound message is parsed, risk-scored, and matched to the right contact and company before your team touches it.

01

Email in. Context assembled.

Inbound email lands, gets matched to the contact and company record, and every prior conversation is pulled. Risk level and intent are tagged before anyone opens the thread.

02

AI drafts using what it actually knows.

The draft is built from 5 layers: your system behavior, org policy, knowledge base snippets, conversation history, and a structured output schema. Confidence score and risk flags are always surfaced — never hidden.

03

Agent edits. Everything is captured.

When your team modifies the draft and sends, Work Hat runs a 3-step analysis: word-level diff, heuristic classifier, LLM verification. Edit type (tone, policy gap, factual error, full rewrite) and intensity score are stored permanently.

Features

Built for the ops lead who runs the whole support system

01

Context-aware AI drafts

Every draft reads the full customer history, company tier, account owner, and your org policy. Not just the last message.

02

Edit analysis pipeline

3-step analysis on every send: diff → heuristic classification → LLM verification. Stores edit type and intensity permanently.

03

AI improvement dashboard

Acceptance rate, edit intensity, edit reason breakdown, and QA queue — all built from real send data. Not a guess.

04

Knowledge base with semantic search

Policy docs, SOPs, tone guides — stored, versioned, and retrieved by semantic search on every single draft.

05

Risk and confidence scoring

Every thread is scored before your team opens it. Red flags surface automatically. Low-confidence drafts are clearly marked.

06

Multi-agent workspace

Roles: admin, manager, agent, QA reviewer. Invite by email in seconds. Full audit trail per org.

Compare

Why ops leads outgrow the incumbents

Intercom, Zendesk, and Front are built for volume. Work Hat is built for teams that want to know exactly where their AI is failing — and fix it.

Work Hatyou
Intercom
Zendesk
Front
AI draft generation
Context-aware (history + policy + knowledge)
Copilot suggestions
Basic macros + AI assist
AI drafts (no context depth)
Customer context in drafts
Full history, tier, company, policy
Partial — same session
Ticket history only
Thread history
Edit capture + analysis
Yes — type, intensity, classification
No
No
No
AI improvement tracking
Yes — dashboard + QA queue
No
No
No
Knowledge base for drafts
Semantic search on every draft
Article suggestions
Macros + article suggestions
Snippets only
Pricing entry point
Free tier → $49/mo
$74+/mo per seat
$69+/mo per agent
$19+/agent/mo

Comparison based on publicly available documentation and pricing pages as of 2026. Work Hat is independently built and not affiliated with any compared product.

Early access

Join the waitlist

Work Hat is in early access. We review every request and onboard teams that are serious about measuring AI quality in their support operations.

or
Talk to us directly — teddyalbayero@work-hat.com