Production AI, delivered under scrutiny

Delivered

Three production AI capabilities released 30 June 2026. Four engineers over 16 weeks, against a plan of eight engineers over 48. Every score traceable to its inputs.

1. Arrived with

   Manual investor matching across deal types in spreadsheets. No scoring rationale and no audit trail.

2. The hard decision

   Scoring had to be explainable to a regulator and reconfigurable by an administrator, so the model could never be the system of record for a decision.

Delivered

Conviction scoring across four signals and multiple deal types, with a coaching agent that surfaces the right investor before the meeting.

1. Arrived with

   Relationship managers ran on memory. Nothing showed whether an investor was accelerating or stalling.

2. The hard decision

   Data never leaves the client tenant. Extraction, scoring and coaching all run inside the client's perimeter, verified on every call.

Delivered

A four-week discovery and a costed remediation plan, with every finding evidenced in code rather than asserted.

1. Arrived with

   A mature implementation with years of accumulated technical debt, and AI on the roadmap.

2. The hard decision

   Security and compliance controls had to be in place before any agent was enabled.

Delivered

A ten-step patient journey on Health Cloud with HIPAA-grade governance, taken from zero to MVP in four weeks. Intake completion is above 85%, against a 40 to 60% industry benchmark.

Delivered

Eleven Einstein and Agentforce pilots scoped and delivered inside Financial Services Cloud, each with a signed governance posture.

Delivered

A lending platform engineered from the data layer up. Agentic services run across Claude and other models through MCP servers, each model selected per task on cost, speed and data residency. DevSecOps pipelines are built to GDPR, PCI DSS and SOC 2 control expectations.