Fragmented evidence
Signals lived across Salesforce, Gong, Zendesk, Totango, Jira, and linked documents rather than in one dependable handoff.
A state-managed, multi-source RAG pipeline synthesizing signals from 8+ enterprise systems to prepare CSMs for seamless, auditable customer transitions.
Input fragmentation
When Professional Services finished onboarding, CSMs had to reconstruct objectives, commitments, sentiment, and risk before they could take responsible ownership of the account.
That reconstruction duplicated work, produced inconsistent transition messaging, and allowed hidden risks to surface only after the moment for proactive intervention had passed. The problem was not missing data. It was evidence without a governed sequence.
Signals lived across Salesforce, Gong, Zendesk, Totango, Jira, and linked documents rather than in one dependable handoff.
Customer data required role-aware access and PII controls; a useful brief could not expose raw source material indiscriminately.
A briefing had to complete in under 15 seconds to remain viable in a live customer-success workflow.
The system had to serve 1,200+ accounts without trading away grounding quality.
Governed state machine
The architecture moved away from one opaque synthesis prompt and toward explicit retrieval, extraction, synthesis, and validation states.
Parallel retrieval gathers opportunity data, conversation signals, support history, and open delivery risks under the user's existing access.
Given an Opportunity ID, a dedicated step locates the linked SOW and Order Form, parses contractual details, and returns a strict JSON payload.
The orchestrator resolves the inputs into confirmed objectives, current health, known risks, and alignment gaps — a brief a CSM can inspect rather than a raw transcript dump.
Faithfulness is scored against a golden dataset before delivery or CRM write-back. Failed checks route to human review instead of passing uncertain output downstream.
Design decision
The initial monolithic prompt hit context limits, hallucinated edge cases, and returned inconsistent structures. Moving to strict state transitions and JSON contracts cost roughly 200ms per briefing; in exchange, grounding accuracy measured against the golden dataset improved 40%, and hallucinations fell to near-zero in the production workflow.
Inspectable brief
The CSM receives a structured account view with objectives, health, risks, gaps, and the control state that determined whether the brief could be delivered.
Explore how a multi-agent orchestration pattern can coordinate customer context, readiness checks, and structured transition briefings across connected systems.
Explore a related simulated operating modelSystems modeled
Salesforce / Totango / Zendesk / Gong / Provisio / Google Drive / Slack
Simulation disclosure: This didactic exhibit uses illustrative data to demonstrate an operating pattern. It is not historical production telemetry.
Sourced outcome
The evidence receipt distinguishes publishable proof from disclosed supporting context, keeping the outcome legible without presenting simulation as historical evidence.
Evidence dossier
Approved visitor-safe summary derived from the evidence ledger. Sanitized depictions remain separated from production telemetry.
Ledger source: docs/proof/evidence-ledger.md
Publication classes: Public, Sanitized depiction
14 Days
Earlier warning window for renewal-risk accounts
40%+
Adoption growth before the workflow became the standard handoff path
<2%
Hallucination rate across 1,200+ generated briefs
My role
I defined the evaluation harness, designed the RAG retrieval strategy, and integrated the final output into the CS team's daily operational tools. I also established the prompt libraries and quality-monitoring framework behind that adoption growth.