growth

Outbound that knows the whole customer.

Segmentation lives in the warehouse, intent lives in product events, consent lives in the CRM. Your agent composes the audience case by case, drafts the message from real context, and returns a governed send list — raw PII never enters the prompt.

Why it works here

Customer outbound messaging, the Contextually way.

Segments no one pre-built

"Usage dropped, renewal inside 60 days, no open ticket" is one sentence to your agent — and one purpose-written program in the runtime. No waiting on a list pull.

PII-safe personalization

Merge fields resolve at send time inside the runtime. The model works with masked handles; names, emails, and account details never transit the context window.

Consent enforced, provably

Suppression and consent lists are applied in-runtime on every send list — and the audit ledger shows they were, which is what your compliance review actually asks for.

The flow of data
snowflake.usage_trend 2,204,118 rows postgres.accounts 214,188 rows suppression.global_optout 86,441 entries contextually runtime segment + draft · merge fields masked PII masked · consent enforced send list · 1,412 692 tokens → context
The program, case by case
goal → win-back audience: usage drop, renewal inside 60 days, consented
usage = sql("snowflake", "SELECT account_id, drop_pct FROM usage_trend WHERE drop_pct > 0.4") crm = sql("postgres", "SELECT account_id, renewal_date, consent FROM accounts") aud = join(usage, crm).filter("renewal_date < 60d AND consent = true") drafts = draft(aud, template="win_back", merge=["first_name","plan"], mask=true) return send_list(drafts, channel="email", suppress="global_optout")
audience of 1,412 accounts · PII masked in-runtime returned send list + 3 draft variants · 692 tokens → context
Get started

See it on your data.

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