# ADR-0001: Build the MQL enrichment service rather than buying

- **Date:** 2025-10-22
- **Status:** accepted
- **Reversibility:** medium (rebuild against vendor would require ~6 months and cost $1.2-1.8M; not impossible but expensive)
- **Deciders:** {{exec_vp_revops}}, RevOps-AI eng lead, {{cutting_edge_saas_company}} CFO (cost approval), Compliance Engineering (consent posture review)
- **Scope:** instance

## Context

{{cutting_edge_saas_company}} runs ~12,000 inbound MQLs per quarter from paid acquisition channels. The existing routing was rule-based on territory only; SDRs spent ~22% of qualifying time re-researching firmographic and intent signals that vendors could in principle provide.

Three vendors were evaluated 2025-Q4 ({{vendor_a}}, {{vendor_b}}, {{vendor_c}}) plus a build option. Decision deadline 2025-11-01 (FY26 budget commit).

Upstream constraints:

- L0 strategy demands a primary metric of SDR-accepted-MQL rate >= 42% (vs. 27% baseline)
- L2 philosophy demands consent-flow integration with {{cutting_edge_saas_company}}'s consent service (Red Line 1)
- {{cutting_edge_saas_company}}'s closed-won customer corpus encodes intent-signal weighting that no vendor can replicate without ingesting that corpus (which would breach the L2 PII tenant-only rule)

## Decision

Build the enrichment service in-house, mirroring components from `{{platform_team_name}}/ai-kit` for shared infrastructure (prompts, eval harness, guardrails, telemetry).

## Options considered

### Option A: Build [CHOSEN]

- **Summary:** RevOps-AI team builds the enrichment service consuming {{platform_team_name}}/ai-kit components; intent-signal weighting derived from {{cutting_edge_saas_company}} closed-won corpus
- **Pros:**
  - Intent-signal weighting trained on proprietary closed-won corpus; competitive moat
  - Consent flow integrates natively with {{cutting_edge_saas_company}}'s existing consent service; no third-party data movement
  - Cost trajectory predictable ($420K annualized; scales with platform team's kit improvements)
  - Reproducibility quadruple pinning straightforward (we own every component)
- **Cons:**
  - 4-month build before first canary
  - Requires sustained RevOps-AI eng capacity (4 engineers); opportunity cost
  - Eval baseline must be built from scratch

### Option B: Buy {{vendor_a}} (firmographic-only)

- **Summary:** {{vendor_a}} provides firmographic enrichment; we layer rule-based intent on top
- **Pros:** Live in 6-8 weeks; vendor handles firmographic data quality; lower headcount cost
- **Cons:** No proprietary intent signals; vendor data passes through their infrastructure (PII tenancy concerns; would require Compliance review extension); {{vendor_a}}'s closest competitor is {{cutting_edge_saas_company}}'s own competitor in adjacent product line - awkward but not blocking

### Option C: Buy {{vendor_b}} (firmographic + intent)

- **Summary:** {{vendor_b}} provides firmographic + intent; full vendor-managed
- **Pros:** Live in 4-6 weeks; vendor handles intent signal modeling; lower per-call cost ($0.05 advertised vs. our $0.08 ceiling)
- **Cons:** Intent signal model is generic; cannot ingest {{cutting_edge_saas_company}}'s closed-won corpus; weighting is industry-average not {{cutting_edge_saas_company}}-specific. Trial enrichment on 200 historic MQLs scored 31% SDR-accepted (below 42% target). Vendor would not commit to a custom training run.

### Option D: Buy {{vendor_c}} (premium, custom)

- **Summary:** {{vendor_c}} offers custom intent model trained on customer corpus
- **Pros:** Custom training; enrichment quality could match or exceed build option
- **Cons:** Cost $1.6M Year 1, $900K Year 2+ (4x build option); custom training requires ingesting our PII corpus which Compliance Engineering rejected on first review; vendor would require {{cutting_edge_saas_company}} to sign a Data Processing Addendum extending PII scope outside our preferred boundary

## Rationale

Option D is rejected on PII boundary; Compliance Engineering blocked on first review. Option C's trial enrichment scored below target; the generic intent model does not match {{cutting_edge_saas_company}}'s customer shape. Option B is feasible but does not address the intent-signal moat; we would still need to build that layer ourselves, eliminating the buy advantage.

Option A is the only path that achieves the 42% target while respecting the PII boundary and producing a competitive moat. The 4-month build cost is real but bounded; the opportunity cost is offset by the long-term advantage of owning the intent-signal weighting.

Tradeoff explicitly accepted: 4-month delay to live deployment vs. intent-signal proprietary advantage and PII tenancy compliance.

## Consequences

### Positive

- Intent-signal weighting trained on proprietary corpus; durable competitive advantage
- Consent flow integrates natively; GDPR Art. 7 + 17 obligation met cleanly
- RevOps-AI team builds AI-shaped capability that will support adjacent functions in future (account-scoring v2, opportunity-stage-routing)
- Reproducibility quadruple pinning straightforward

### Negative

- 4-month build; first canary 2025-11-08 vs. potential mid-September with vendor
- Sustained RevOps-AI eng capacity required (4 engineers + occasional Platform Engineering pairing)
- Eval baseline built from scratch (~3 weeks of dataset curation)
- Mirror-sync discipline must be maintained against {{platform_team_name}}/ai-kit; drift is a real risk (currently 14 days drift; tracked)

### Followups

- Define eval methodology and dataset curation process (`policies/framework-contract.md`; ADR-{NNNN} for eval methodology if non-trivial decisions surface)
- Establish kit-mirror discipline with {{platform_team_name}} (`decisions/ADR-0002-kit-mirror-direction.md`)
- Compliance review of consent-flow integration before first canary (`decisions/ADR-0003-consent-flow-integration.md`)
- Set up inbox-outbox pair with {{platform_team_name}} for kit-mirror sync events and capability requests

## Reproducibility note

Decision rests on:

- Trial-enrichment results from {{vendor_b}} on 200 historic MQLs (vendor-side run; data preserved in `revops-ai-eval/vendor-trial-2025-10/`)
- {{vendor_c}} cost quotes (preserved in `revops-ai-eval/vendor-quotes-2025-10/`)
- Compliance Engineering review notes on Option D PII scope (Confluence > `revops-ai/compliance-reviews/2025-10`)

If vendor pricing or capabilities change materially, re-evaluation may be warranted. Re-evaluation produces a new ADR; this one stays on record.

## Cross-references

- Layer this decision affects: L0 (strategy), L4 (platform kit posture)
- Related ADRs: ADR-0002 (kit mirror direction); ADR-0003 (consent flow integration)
- Inbox entries: none (decision predates inbox topology setup)
- Session logs: pre-deployment session logs in `revops-ai-archive/2025-pre-deploy/`
