Intent bar
Capture goals in natural language with structured commands.
AI-enabled work automation
Give your customers and teams one front door — and never lose a request again.
Threada turns unstructured work — requests, documents, and review queues — from any channel into grounded answers or governed actions across your business systems, with full traceability from ask to outcome.
Ship purpose-built outcomes by enabling a pack, then adapt templates, policies, and connectors.
How it works
The same flow works for every department and use case.
1
Connect a channel
Start with web, then add Slack, email, in-app, or API channels as you expand.
2
Define policies and routing
Set what AI can answer, what needs approval, and when to escalate to a human.
3
Requests become WorkItems
Every request becomes a tracked record with full context, extracted details, and an audit trail.
4
Review and execute
AI proposes actions. Humans approve when needed. The system executes safely.
5
Measure real outcomes
Track containment, resolution time, action success rates, and ROI — not just message-volume metrics.
Where teams use Threada
Customer operations
Resolve common requests from your knowledge base, or create a complete escalation package for the workspace — with full context attached.
Security questionnaires and RFPs
Answer vendor questionnaires and security reviews with strict citation mode and exportable evidence bundles.
IT and procurement requests
Turn Slack messages and emails into structured requests with approval workflows, policy checks, and tracked outcomes.
Contract and proposal review
Extract key terms, flag deviations from your playbook, and route to the right reviewer with complete context.
Why teams switch from general-purpose AI to Threada
Model-agnostic by design
Use the best model for each task. Switch providers without re-architecting. No vendor lock-in to a single LLM.
WorkItems, not disposable threads
Every request becomes a stateful record with lifecycle, ownership, evidence, and action history — not a short-lived thread that vanishes when the tab closes.
Policy controls, not just prompts
Route, approve, restrict, and audit with versioned policy overlays. Prompt engineering is one input, not the entire governance model.
Execution you can trust
Actions run through allowlists with idempotency, retries, and rollback controls. Not ‘varies by integration.’
Outcomes over vanity metrics
Track containment, resolution time, approval cycles, and action success — the metrics that prove ROI to leadership.
Enterprise-ready from the start
Tenant isolation, RBAC, SSO, audit trails, and evaluation gates are built into the control plane — not bolted on later.
Connects to the tools you already use
Governed integrations with Zendesk, Jira, Slack, and more — with scoped credentials and auditable execution.
The five interaction surfaces of AI-native work
Threada keeps every workflow reviewable with five connected interaction surfaces.
Canvas
Build drafts, plans, comparisons, and dashboards in one workspace.
Evidence drawer
Trace sources, rationale, and diffs behind every recommendation.
Action controls
Approve, schedule, automate, or roll back with explicit guardrails.
Run log
Audit every human and agent step with searchable timelines.
Choose the right shell for the job
Work, Life, and Studio share one core runtime but keep trust posture and UX clear.
Work
Governed execution for enterprise operators.
Outcomes: queues, approvals, run monitoring, and exception handling.
Connector families: identity, systems of record, communication, automation.
Life
Consumer/prosumer planning with lighter trust framing.
Outcomes: personalized plans, compare flows, versions, and share controls.
Connector families: maps, booking/data feeds, payments, messaging.
Studio
Builder plane for pack design, policy controls, and release workflows.
Outcomes: pack authoring, evals, connector scopes, versioning, publish/rollback.
Connector families: tool runtimes, knowledge sources, and intake channels.
Start with a pack/workspace
Ship purpose-built outcomes by enabling a pack, then adapt templates, policies, and connectors.
Trust and governance by default
Policies, approvals, evidence, and rollback are first-class controls across shells.
No super-app ambiguity
Position each pack as a focused product while reusing the shared core runtime.
Who adopts first
Operations and CX workflows
Deflect routine questions with evidence. Route exceptions as complete work packets that reduce handle time.
IT and shared services
Standardize intake, triage, and approvals across internal IT, procurement, and legal request workflows.
Security and trust teams
Auto-answer vendor questionnaires and RFPs with strict citation mode and exportable audit trails.
Operations and compliance
Collect evidence continuously, map controls to artifacts, and draft audit-ready narratives.
Multi-tenant operators
Run many isolated workspaces with consistent controls, shared workflow templates, and portfolio reporting.
Frequently asked questions
Where should we start?
Pick one high-volume workflow and launch it in a single channel first. Prove that answers are accurate and escalations reach the right people, then expand to more channels and packs.
How is Threada different from ChatGPT or Gemini for business?
ChatGPT and Gemini are general-purpose AI copilots tied to one vendor's model. Threada is a purpose-built work automation platform: every request becomes a trackable WorkItem with policy controls, execution guarantees, and outcome analytics — across any LLM.
Do we need to replace Zendesk, ServiceNow, or Salesforce?
No. Threada works alongside your current tools. It captures and structures requests, then pushes enriched work packets and executes approved actions in your existing systems.
Can AI really handle the edge cases that broke our last automation?
AI handles understanding and structuring. Policy controls, review queues, and approval steps handle the exceptions. Humans stay in the loop for anything high-risk.
What can we actually measure?
Containment rate, time-to-resolution, escalation quality, approval cycle time, action success rate, and cost savings — not just how many interactions happened.
How do we evaluate safety before going live?
Run evaluation gates that test extraction, routing, grounding, and action behavior. Roll out gradually with canary traffic, shadow mode, and one-click rollback.