Join the customer history across systems, then ask in plain English and inspect the evidence behind the answer.
Count people with Call booked, then Deal signed within 30 days. Check an AI answer against those outcome records.
Drafted from your source definitions. Review before saving.
A dedicated team builds it with you. Start with one decision.
One record, then the question.
Your team brings one decision. Our dedicated team connects the sources and builds it with you.
Support and billing records can join through your warehouse or our API as build scope. Connecting your existing LLM is also scoped in the build.
Ask AI reads profiles, visits, sessions, events and conversions. Check CRM steps and call results through outcome counts and their records.
Should we be worried about the Hartley account?
It read one system, found a paid invoice and answered no. It never saw the three support tickets or the stalled renewal.
READ: BILLING ONLYGlued, the invoice, the tickets and the stalled renewal sit side by side, each with its source. That is the context the answer was missing.
DEMO SCENE. Hartley is fictional. Support desks and billing join through your warehouse or our API, as part of the build.
On the call, we map one outcome and the systems it needs. A dedicated team builds it with you.
Scoped and priced to the outcome, agreed before work begins. No seat licences.
A dedicated team builds the context. Ask AI in the Glue Console shows the sources it read.
Join visits, forms, bookings, CRM steps and email on the person. Keep the source on every fact. Connect only what the question needs.
Ask in plain English. Each answer lists the profiles, visits, sessions, events and conversions it read. Check CRM history through outcome records.
What did Sarah do before she booked?
Open an outcome count to its records. Check the people, time window and source behind a number before acting on an answer.
Set capture switches with an audit trail. Mask replay input by default; keep approved contact fields only. Payment details and passwords are not captured.
As part of an Outcome Build, we can wire the context into the AI tools your team already uses.
On the call, we find which systems hold the missing context today. In the Outcome Build, a dedicated team glues it and puts it in front of the people who ask.
The same model can feed your LLM, BI tool or destination. We agree each connection in the build.
Scoped and priced to the outcome, agreed before work begins. No seat licences.
You don't need the answer, only the question.
