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How It Works

Built for real workflows,
not conversation demos.

The system breaks each request into clear steps: understand what's being asked, find the right context, check eligibility, take action, and confirm the outcome. Every layer runs within your defined rules and leaves a full audit trail.

Live
OverviewWorkflowsIntegrationsAlerts
MA

Agent Tickets

+12%

1,284

vs yesterday

Directed Traces

+8.3%

892

vs yesterday

Automation Rate

+2.1 pts

94.3%

vs last week

Avg Resolution

↓ 0.8s

2.4s

faster

Automation Rate

% resolved without agent intervention

94.3%

current

MonTueWedThuFriSatSun

Workflow Volume

Tickets processed per day

1,284

today

MonTueWedThuFriSatSun

Integrations

Zendesk API48msOK
Shopify31msOK
Stripe62msOK
Intercom55msOK

Last check: 12s ago

By Source · Today

Zendesk578
Shopify411
Stripe193
Intercom102
Return request#84208 · Zendesk
Processing
Order modification#84207 · Shopify
Resolved
Subscription cancellation#84206 · Stripe
Review
Refund dispute#84205 · Zendesk
Resolved
Wrong item received#84204 · Shopify
Resolved
Billing query#84203 · Stripe
Resolved

Showing 6 of 1,284 workflows · Today

Automated: 1,210  ·  Review: 74

Every workflow follows this sequence. Each layer is configurable, observable, and operates within your defined rules.

How each layer works

The system is composed of discrete, observable layers. Each has a defined role. None operates as a black box.

01

Planning

Receives the request and works out the right sequence of steps to resolve it. Breaks complex workflows into ordered tasks and manages execution from start to finish.

Example: A return request triggers: verify order, check return window, apply exception rules, determine action, draft or send response

02

Context and policy lookup

Pulls the documents, policy sections, and order context needed to handle the request correctly. Filters for relevance and passes the right information to the action layer. Everything is built from your own documentation, not assumptions.

Example: Returns policy fetched, filtered to the applicable clause for the product category and purchase date

03

Actions in your systems

Carries out real operations in your connected platforms. Reads order data, updates records, issues refunds, generates return labels, closes tickets. Every action is logged in full, before and after it runs.

Example: Refund issued via Shopify API. Return label generated. Zendesk ticket closed. All within the same workflow run.

04

Human review and control

Set which workflows need a human to sign off, at what thresholds, and who gets the request. Drafts queue for review before anything is sent. Every decision, whether automated or signed off by a person, goes into the audit log.

Example: Refunds above £200 require agent approval. Standard return label generations proceed automatically.

05

Connecting to your tools

Connects to your helpdesk, ecommerce platform, CRM, and internal systems via API. Actions run with the right permissions and leave a structured record for review, reporting, or compliance.

Example: Shopify, Zendesk, Salesforce, and internal order management systems, all reachable within a single workflow run

Control layer

You define what runs automatically and what requires a human

The system operates within explicit rules, not inferred preferences. There is no ambiguity about when automation applies and when a human is required. Every control mechanism is configurable, documented, and auditable.

Most teams start with co-pilot mode, with every draft reviewed before anything is sent. They expand automation scope incrementally as they verify the output meets their standard.

Approval thresholds

Define which actions require a human sign-off. Set rules by refund value, request type, customer segment, or any combination. Nothing above the threshold runs without review.

Draft-before-send mode

All responses and actions can be queued for review before anything is sent. Agents see the draft and the context behind it, then approve, edit, or reject.

Explicit workflow rules

What the system is allowed to do, in what sequence, and under what conditions is defined explicitly, not inferred. Rules are documented, versioned, and reviewable.

Built from your policy docs

Every response is generated from your actual policy documentation. If the relevant section isn't found, the system flags it rather than guessing.

Exception routing

Requests that fall outside defined parameters are surfaced to the right person, with the full context prepared: what was retrieved, what checks ran, and what the system would have done.

Persistent audit log

Every action logged with timestamp, input, output, and approval status. Queryable across workflows, time periods, and request types. Available for internal review or compliance reporting.

Implementation

Built into your environment, not next to it.

The system is delivered as part of your existing operational stack, it reads from the document repositories, knowledge bases, and review queues your team already uses, and it writes back to the systems where work is tracked. The integration points are agreed during scoping; the implementation is built around them.

01

Document and knowledge sources

PDF, Word, scanned documents, structured forms, internal knowledge bases, and policy repositories. Documents stay in the systems where they live; the workflow reads from them where it needs to.

Compatible with the document and knowledge systems your team already uses

02

Operational systems

Customer requests and case records routed to your existing CRM, ticketing, or workflow tool. Records are updated where the team already works, with full attribution and audit trail.

Common targets: HubSpot, Salesforce, Zendesk, Jira Service Management, and custom internal systems

03

Reporting and visibility

Operational reporting and exception views delivered into the BI environment your operations team already uses, or a purpose-built view when that is the better fit. The audit trail is structured and queryable.

Common targets: Power BI, Looker, internal dashboards, custom views

04

Deployment model

Hosted in your cloud environment, in our managed environment, or on-premise where data residency requires it. The deployment model is decided during scoping, not assumed.

Private model deployment available for workloads where data cannot leave your infrastructure

The internal architecture, model providers, retrieval indexes, workflow orchestration, is selected during scoping based on data sensitivity, latency requirements, and existing security controls. Specifics are documented in the engagement proposal.

Want to understand what this looks like for your specific workflows?

We'll map the architecture against your processes. No generic demo, no generic slides.