Case Study

Your AI Is Only As Good As Your Data

We built the data architecture that makes automation trustworthy — 3 production databases, a 7-step deterministic pipeline, and zero AI inference in the data layer — a core tenet of our deterministic systems approach.

Duplicate contacts across 5 tools

CRM says one thing, email says another, the spreadsheet has a third version. Nobody knows which is right.

Invoices that don't match POs

Manual data entry across disconnected systems. Errors compound silently until someone catches them — or doesn't.

CRM contradicts the spreadsheet

Two sources of "truth" that disagree. Your team picks whichever is most convenient. Decisions built on sand.

Email threads as "system of record"

"Check the email from last Tuesday." That's not a system. That's a liability.

Financial data across 3 places and someone's memory

QuickBooks, bank feeds, and "I think we already paid that." No single number you can trust.

Diagram showing 3-database SSOT architecture with deterministic 7-step intake pipeline connecting email, CRM, and financial systems

Data architecture is not a feature. It's the foundation that makes everything else trustworthy.

SSOT

ike_ops.db

3.8 MB · SQLite WAL

Operational single source of truth

9 Tables
  • messages
  • triage
  • contacts
  • routing_rules
  • intake_bridge_log
  • triage_runs
  • contact_sync_log
  • sent_messages_learned
  • schema_version
SSOT

bookkeeper.db

SQLite

Financial data — clean, reconciled numbers

Domain
  • Invoices & receivables
  • Cash flow tracking
  • Reconciled transactions
  • Financial reporting
SSOT

ops_engine.db

13.2 MB · SQLite

Email triage, contacts, routing rules

Domain
  • Email classification
  • Contact management
  • Routing rule engine
  • Triage automation

Same input always produces same output. Fully auditable. Fully reproducible. Zero AI inference in the pipeline.

1

Normalize

Clean input data. Strip noise, standardize formats, enforce schema.

2

Dedup

SHA-256 content hash for exact matches. Levenshtein fuzzy matching for near-duplicates.

3

Route

Keyword scoring against the rules engine. 300 lines, 6 precedence levels. 90% of emails never touch AI.

4

Q-Score

Eisenhower 2-axis prioritization with financial impact weighting. Urgent + important + money = top of the stack.

5

Persist

Write to the SSOT database. One record, one truth, one location.

6

Link

Cross-reference related records. Contacts to messages. Messages to triage decisions. Full graph.

7

Archive

Immutable audit trail. Every decision, every routing, every score — permanently recorded.

0%
Orphan Rate

Every contact linked. No orphaned records.

0%
Duplicate Rate

SHA-256 + Levenshtein. No duplicates survive.

90%
Emails Routed Without AI

Rules engine handles the volume. AI reserved for the edge cases.

100%
Reproducible

Same input, same output. Every time. No inference drift.

P1 Critical Financial
P2 Customer-Facing
P3 Operational
P4 Internal
P5 Informational
P6 Noise / Archive

Deterministic keyword scoring with cascading precedence. Higher priority rules always win. No ambiguity.

Stop Building AI on Bad Data

Your AI is only as good as your data. We clean it first. Data architecture is not a feature — it's the foundation that makes everything else trustworthy.