AI Systems Deployment for B2B Operations

Industry: B2B Professional Services•Scale: Mid-market firm, 150 employees, $25M ARR

Context

Mid-market firm, 150 employees, $25M ARR

Constraint: Zero external API dependencies, on-premise data residency, sub-100ms latency

Problem

Revenue operations bottlenecked by manual quote generation, inconsistent lead qualification, and reactive pipeline management. Senior staff consumed by routine tasks, preventing strategic work. No real-time visibility into deal progression.

Intervention

Deployed multi-lane AI automation across the revenue pipeline. Implemented policy lattice for approval workflows. Established real-time telemetry for executive visibility. AI systems handle quote generation, lead qualification, and pipeline orchestration end-to-end.

Architecture / System Changes

Interface layer: Executive dashboards with real-time system telemetry

Processing layer: AI runtime executing revenue workflows

Data layer: Encrypted on-premise storage with full audit trails

Governance overlay: Policy engine enforcing approval workflows and guardrails

Outcome

Quote generation cycle time reduced from days to minutes. Lead qualification accuracy improved through consistent automated execution. Pipeline visibility increased from weekly reports to real-time signals. Senior staff capacity freed for strategic initiatives.

What Was Intentionally Not Done

Builds trust through transparency about boundaries.

•Did not replace human sales team — AI handles routine execution

•Did not expose proprietary methodologies — architecture abstracted

•Did not require vendor API integrations — fully sovereign stack

•Did not compromise on security — all data remains on-premise

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