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support · success

Every conversation starts with the full picture.

When a customer writes in, the answer depends on their plan, their usage, their invoices, and their last three tickets — four systems. Your agent assembles the complete picture in seconds and hands your team (or your support agent) exactly the context that matters.

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Why it works here

Customer 360, the Contextually way.

Assembled on demand

No prebuilt 360 warehouse project. The profile is computed fresh from live systems each time, scoped to the question being asked.

Right-sized context

A billing question pulls billing history; an outage question pulls incident logs. The agent decides what belongs in context, case by case.

Powers human and AI support

The same governed assembly feeds a support rep's sidebar or an AI support agent's context — with identical policy enforcement either way.

The flow of data
postgres.accounts + invoices 85 rows snowflake.usage 18,204 rows s3.ticket-history 3 threads contextually runtime scoped assembly · brief() caller's entitlements only account brief 874 tokens → context
The program, case by case
goal → full account context for inbound ticket #48812
acct = sql("postgres", "SELECT * FROM accounts WHERE id = ticket.account_id") usage = sql("snowflake", "SELECT feature, last_used FROM usage WHERE account_id = acct.id") bills = sql("postgres", "SELECT status, amount FROM invoices WHERE account_id = acct.id") hist = scan("s3://support-2026", match=acct.id, limit=3) return brief(acct, usage, bills, hist, max_tokens=900)
assembled from 4 systems in one run returned account brief · 874 tokens → context
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See it on your data.

Book a demo and we'll run customer 360 against systems like yours — your stores, your policies, live — and map the path to a deployment in your VPC.