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AI for customer-support team dem

Turn question dem wey dey come through email, chat, and form into answer wey stand on evidence wey get citation, and action wey get governance — without say you go lose accountability.

Solutions

Customer-support team dem dey handle plenty request wey no get structure across plenty channel. Threada dey arrange dat intake into WorkItem dem wey get type, dey draft answer wey stand on evidence wey cite your knowledge source dem, and dey route di sensitive outcome dem through approval before e go take any action inside di system dem wey connect.

REC WorkItem wey dem dey govern
Intake Typed WorkItem wey get field wey dem comot
Answer E stand on your sources, with citation
Approval Dem pass am through decision step
Action Dem run am for way wey you fit reverse, for di timeline
Dem audit am from start to finish

How Threada take fit your work

  • 01 Wetin dey come through email, in-app, Slack, Teams, and web channel dey arrange into one WorkItem queue wey get status, assignment, and SLA timer.
  • 02 Answer dem dey stand on your knowledge asset with citation, and one clear no-answer fallback dey stop reply wey sure but no get evidence.
  • 03 Operator dem dey triage with saved view, bulk action, response template, internal note, relationship linking, and duplicate detection.
  • 04 Action wey get governance — create, update, tag, comment, notify — dey run behind approval gate, with execution wey you fit reverse and wey dem dey audit.

Wetin you fit do today

01

Intake channel dem wey get type, with provider verification and policy override for each channel.

02

WorkItem queue dem with assignment strategy, routing rule, and SLA target for first-response, next-response, and resolution.

03

Copilot suggestion dem, response template wey get variable, and draft wey stand on evidence with citation.

04

Predictive operations: SLA risk prediction, volume forecast, anomaly detection, and churn-risk signal.

05

Feedback and scorecard dem with deflection, fallback rate, and CSV/NDJSON evidence export.

How di work dey normally flow

  1. 01

    Customer email abi chat go land, e go arrange into WorkItem with field dem wey dem don extract.

  2. 02

    Retrieval go draft answer wey stand on evidence with citation, abi e go return question wey go clear di matter when di intent no clear.

  3. 03

    Operator go review am, edit am with response template, then either reply abi propose action wey get governance.

  4. 04

    Sensitive action dem dey route through approval gate, dey execute for way wey you fit reverse, and dem dey record am for di timeline.

Waka inside di platform

WorkItemsEvidenceActionsPricingGeneration wey retrieval dey boost (RAG)

Question dem wey people dey always ask

Which channels I fit automate customer-support intake from?
Threada dey take typed intake from web, in-app, Slack, Teams, email, API, and custom endpoints; inbound provider channels include Gmail, Twilio SMS, WhatsApp, social, Discord, and Teams webhooks, wey dem all normalize into WorkItems.
How I go take stop AI support answers from being fabricated?
With abstain mode on, Threada dey use relevance threshold and dey return clear no-answer fallback instead make e fabricate answer, and any answer wey e produce dey get citations.
How approvals dey work for support actions?
Threada fit gate support actions like updating ticket or notifying customer behind decision steps; dem dey record approvals, actions dey reversible with idempotency keys, and dem dey capture execution as history wey dey auditable.

Bring AI automation wey get governance come your team

Waka inside di platform abi talk to our team about your workflow dem.

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