VegradeAI engineering
Real estate6–10 week production programIllustrative program

Policy-bound outbound lead agent

Real estate teams need velocity without brand risk. This program shape pairs a multi-step agent with deterministic business rules, evaluable generations, and operator tooling so marketing and ops can iterate safely as seasons and inventory change.

Challenge

Inbound lead volume spikes after marketing spend, but qualified tour bookings do not keep pace—manual follow-up cannot scale, and ungoverned automation creates brand and compliance risk.

Approach

Policy-bound outbound agent across SMS and email with CRM sync, tone guardrails, and explicit opt-out handling—plus dashboards for managers to tune scripts without redeploying code.

Architecture & delivery

  • Workflow engine for follow-up cadences with business-hour enforcement
  • Policy layer separating LLM copy from irreversible side effects
  • Feature flags for script variants and regional experiments
  • Manager console for approvals, overrides, and sampling review

Governance & controls

  • TCPA-aligned consent and suppression lists with audit exports
  • PII minimization in traces; configurable retention windows
  • Role-based access for scripts, secrets, and customer records

Operational outcomes

  • CRM writes with idempotency keys and replay-safe webhooks
  • Daily eval reports on tone, compliance phrases, and conversion proxies
  • Canary releases by region before national enablement
  • Runbooks for incidents, including manual takeover paths

Programs of this shape shift follow-up from best-effort to consistently timed, measured sequences. Ops can see where drop-off occurs and adjust prompts with guardrails intact—reducing escalations while lifting qualified tours in a treatment cohort.

Illustrative content. This brief describes a reference program shape—architecture, governance, and target outcomes drawn from common industry patterns. Vegradeis pre-launch on named client references; numbers shown are targets we design toward and depend on data readiness, baselines, and adoption in any future engagement.