Know where your data
meets AI — before it costs you.
Boldingbroke maps where sensitive information enters your AI workflows, identifies the governance gaps, and delivers a prioritized remediation plan. For regulated organizations that need answers, not another platform to buy.
Led by Sharon L. Bolding, PhD — global AI compliance-surveillance work at Citi · PhD in linguistics · multiple-time company co-founder.
The AI Data Exposure Assessment
A focused, fixed-scope engagement. In eight hours we map your exposure and hand you a plan your team can act on — before you spend on tooling that may be aimed at the wrong problem.
Eight hours · fixed scope · fixed fee
- Workflow map — where sensitive data enters your AI tools
- Exposure findings — the gaps that matter most
- Prioritized controls — what to fix, in what order
- 30-day action plan — concrete next steps
Tailored to your regulatory reality
The assessment is shaped around the rules you actually operate under.
Evidence first, then a plan
When evidence-based tracking is warranted, we deploy Parsifer — our patent-pending semantic-fingerprinting platform — to see where protected material surfaces in AI outputs. But the engagement starts with strategy, not software.
Map
We trace how your teams actually use AI and where sensitive information flows in.
Assess
We identify the governance gaps and rank them by real-world risk and effort.
Plan
You get a prioritized set of controls and a 30-day action plan — with or without new tooling.
AI-induced risk is real and present
Independent research on what’s already happening inside organizations.
Policy violations / month
Average organization vs. top-quartile organization.
Types of data leaked
Source code · regulated data · intellectual property.
Employees using AI
Entered internal process information into AI tools.
Source: Moody’s Risk and Compliance 2025 Survey.
Advisory grounded in real compliance work
Sharon L. Bolding, PhD is a business-operations, product-strategy, and technical specialist focused on AI and cybersecurity, with a research background in NLP and machine learning. At Citi, she led the team that implemented an AI platform for compliance surveillance, including a risk model in 42 languages.
She has advised companies on growth strategy across fintech, healthcare, cybersecurity, and AI, has co-founded multiple companies, and has taught at the University of Washington and Seattle Pacific University. PhD in Linguistics, University of British Columbia.
Book an AI Data-Risk Assessment
Tell us a little about your organization and we’ll be in touch to schedule. Honest advice and a clear plan — before you spend on the wrong solution.