Enterprise AI Case Studies

A Series C payments platform allocated 73% of engineering sprint capacity to maintaining legacy features while AI infrastructure costs scaled 4x faster than user growth.

Deployed the Product Debt Index (PDI) audit. Identified 31 negative-carry features generating context rot and consuming $70,000 monthly in dead token traffic.

Depreciated 31 legacy routes, restricted non-deterministic LLM calls to gated XML contracts, and redirected engineering resources to core margin-generating workflows.

PDI dropped from 78 to 34. $840,000 in recurring OpEx redirected to revenue-generating features over 12 months.

A B2B analytics vendor experienced token bill expansion from $3,100/mo to $14,200/mo due to exponential retry loops and unstructured prompt bloat.

Utilized AI Unit Economics Benchmark (AUEB) to isolate context rot and recursive agent loops failing silently during JSON parsing.

Installed Exogram runtime cost-caps and deterministic schema validation at the API gateway layer, enforcing strict context XML boundaries.

Monthly API spend dropped from $14,200 to $2,900 with zero reduction in accuracy and zero latency impact.

A private equity sponsor evaluating a $42M B2B platform required verification of claimed R&D capital efficiency prior to deal sign-off.

Conducted an executive R&D Capital Audit, discovering $4.2M in uncapitalized infrastructure debt, vendor lock-in risk, and missing evaluation pipelines.

Delivered board-ready audit report quantifying the debt liability and structuring a deterministic remediation roadmap.

Sponsor successfully renegotiated deal valuation downward by $375,000, achieving a 50x ROI on audit cost ($7,500).