Resolve
Automated support across messaging
Most of your ticket volume is the same dozen questions asked in different words. Resolve answers those in seconds, from your policies and your order data — and hands over everything else with the context already assembled.
- Verified answers for your highest-volume query types
- One agent operating across WhatsApp, email, and web chat
- Context-preserving handoff, so customers never repeat themselves
Illustrative interface. Not real customer data.
The long tail is not the problem. The short tail is.
Where is my order. Can I return this. Does it fit. Is it in stock. A handful of intents make up the bulk of the queue, and your team answers them thousands of times a month instead of doing the work that needs judgement.
Rule-based bots made this worse, not better — they intercept the customer, fail to answer, and hand over a conversation the human now has to restart. Resolve only takes the conversations it can actually finish, and gets out of the way early on the ones it cannot.
What Resolve actually does.
Verified answers
Responses are grounded in your policy documents, catalog, and live order data — each one traceable to the source it came from.
One agent, every channel
The same brain on WhatsApp, web chat, email, and SMS. Consistent answers regardless of where the customer starts.
Order-aware actions
Not just answers — check status, process a return, reschedule a delivery, apply a credit, all inside limits you define.
Context-preserving handoff
When a human takes over they get the transcript, the customer record, the agent's reading of the intent, and why it escalated.
Tone and policy control
Your voice, your escalation rules, your refusals. Configurable per channel and per queue.
Coverage analytics
A running list of what the agent could not answer, ranked by volume — your roadmap for what to ground next.
From connected to live.
Four stages. The first two are where the real work is; the rest is calibration.
Ground it
Policies, macros, help centre articles, and catalog data are loaded and structured. Conflicting or outdated content surfaces here, which is usually the first useful output.
Set the boundaries
Decide what the agent answers alone, what it verifies before acting, what it must never do, and the value thresholds where a human signs off.
Deploy behind a queue
Go live on one channel with responses reviewed before sending. You see real quality on real traffic before it is autonomous.
Widen coverage
Release the review queue for intents that hold up, and use the coverage report to decide what to ground next.
Where teams point it first.
Order status and tracking
The highest-volume query in commerce, answered from live fulfilment data instead of a copy-pasted link.
Returns and exchanges
Eligibility checked against your policy and the actual order, then processed end to end.
Product and fit questions
Answered from the catalog and your own sizing guidance, not from a general-purpose model guessing.
Account and billing
Invoice copies, address changes, subscription pauses — routine account work with an audit trail.
What you will be able to measure
Deflection alone is a vanity metric if satisfaction falls. Resolve reports both sides.
Auto-resolution rate
Conversations closed without a human, by intent.
First response time
Across channels, including out of hours.
CSAT on automated conversations
Tracked separately from human-handled ones, so you can see the gap.
Handoff quality
How often a human has to re-ask the customer something.
Coverage
Share of incoming intents the agent is grounded for.
Cost per contact
The number the finance conversation actually turns on.
Sits on top of the stack you run.
Prebuilt connectors for the common systems, and an integration path for the ones that are yours. Nothing here asks you to migrate.
Do not see yours? Ask us — most integrations are a connector, not a project.
Resolve, answered plainly.
What happens when it gets something wrong?
Two defences. First, answers are grounded and cited, so a wrong answer is traceable to a wrong or missing source document — which you can fix once, permanently. Second, confidence thresholds and restricted-action rules mean the agent escalates rather than improvises when it is unsure.
During rollout, the review queue means a human approves responses before they send, so you calibrate on real traffic without exposure.
Does this replace our support team?
It replaces the repetitive part of their queue. The realistic outcome is that the same team handles more volume and spends its time on the conversations where judgement, empathy, or negotiation actually matter. If your plan is to cut headcount to zero, we are probably not the right fit — someone still needs to own the escalations and the policy.
Which languages does it handle?
The agent handles multilingual conversations, including code-mixed messaging common in Indian markets. Quality depends on how well your source material covers the language — grounding documents in English while customers write in Hindi limits what it can verify. We test this explicitly during scoping.
Does our helpdesk stay the system of record?
Yes. Resolve reads from and writes back to your helpdesk — conversations, resolutions, and tags land where your reporting already lives. We are not asking you to migrate your ticketing.
Bring a real workflow. We will show you Resolve running on it.
Thirty minutes, your data, no slideware. If it is not the right module for your bottleneck we will tell you which one is.