Boldingbroke
Smarter Information Strategy—Without Paying Twice for AI
“You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful.”
Satya Nadella, The Reverse Information Paradox
Today’s information advantage belongs to you alone, creating a moat defending your business. Don’t let AI companies profit from your secret sauce—proprietary information, operational data, strategic patterns, and trade secrets that your competitors don’t have. Frontier models represent a channel through which these defensible information advantages leak outward, becoming part of consensus knowledge that competitors can also access. Don’t solve today’s problems by mortgaging tomorrow’s competitive ground.
Semantic DLP: Protecting Data for Better Intelligence
What can you actually do with what you have—internal systems, data, resources?
AI-Induced Risk is Real and Present
AI companies, data aggregators, bots—they all exploit your data to build multi-billion $$$ businesses with little or no scrutiny.
223 Average Org
2100 Top Quartile Org
42% Source Code
32% Regulated Data
16% Intellectual Property
62% Entered internal process info
48% Entered non-Public Org info
Statistics from: Moody's Risk and Compliance 2025 Survey
Boldingbroke is an external check on AI systems, not an AI wrapper. Learn more about how we reduce the risk of AIs exploiting your institutional trade secrets.
In order to know how AI and data aggregators use your assets, you need a strategy. You need a way to regain control of your valuable IP and ensure that AI is a benefit rather than a threat.
At Boldingbroke, we specialize in Cybersecurity and AI: Strategy and advising on productization of technology in a way that is sustainable and ethical.
Boldingbroke provides solutions to identify and track AI and data usage within your firm; assessing risk, applying policies to mitigate and prevent data loss. DLP is our DNA.
Data Identification and Tracking—How It Works
Our service—Parsifer—is based on a patented technology for semantic fingerprinting of data and querying AI models for risk evaluation.
Integrate Parsifer into your processes for full logging, access controls, and monitoring aligned with your compliance standards. The Parsifer platform uses a four-step process to identify and track your specific source data:
Semantic Fingerprinting – the process starts by analyzing a sample of your work to generate a semantic fingerprint of its characteristics: a unique DNA signature for the data. This fingerprint features metadata that represent source content.
Policy and Regulatory – The platform, through APIs and connectors, imports the latest regulatory guidance, as well as internal policies defined by your legal and compliance teams. These guidance materials are parsed and fingerprinted in the same way as above, in step one. These frameworks and rules standardize access and infuse controls upon critical data assets.
Data Management – The platform provides a ‘start-to-archiving’ governance tracking timeline tied to the audit trail and system logs. As an employee uses AI system outputs based on prompts and analysis, Parsifer records the entire data lifecycle across different models, processes, and storage modalities.
Audit Trail – System logs don’t tell the whole story. For true compliance, you need a record of real-time activity that a regulator will accept as proof of best effort. The only way to create a tamper-resistant data artifact is to show the work that has been done, by whom, and when — the prompts, responses, model versions, and so forth. Then encrypt the data at rest and in transit. Parsifer also provides the option to store the fingerprint and audit trail on chain.
AI Risk Analysis
Fact: AIs have pretty much swallowed the world’s digital content, including IP under copyright and behind paywalls.
Fact: as a consequence, your IP – financial, research data, training manuals, professional journals – are somewhere inside one LLM or another.
Fact: you’re losing money, reputation, and competitive advantage as a result with lower client engagement, increased regulatory exposure, and insider threats.
AI Companies Want Indiscriminate Use of Your Data
Focused on market grab
Transparency undermines their strategy
Regulatory compliance adds friction to deployment and scaling
AI companies will avoid regulatory frameworks until forced to comply:
Then acquire best-in-class solution only when compelled
Who needs the Parsifer Solution?
Financial Sector: Banks, credit unions, crypto platforms, mortgage companies, they’re all highly regulated. And by their very nature require risk management controls. Data governance is the bedrock of Compliance. Any decision that materially impacts a customer, a transaction, or a regulatory obligation must be explainable. Change management, audit trails, and access controls are all subject to inspect. Where is your data? Who has access? What did they do and when? Question and more that must be supported with timely proof of work. Parsifer knows and can ease your oversight and audit journey with reports, analytics, timelines and more.
Health Sector: Health and research data are subject to numerous regulations such as HIPAA and GDPR. Any exposure to AI agents and services can breach controls, breaking compliance and public trust.But the promise of AI can also lead to better outcomes, faster insurance claims processing, and resubmittal. Clinicians and researchers are skeptical of AI usage when the product of those AI models are biased or inaccurate, which also undermines trust.With proper data governance and quality control, Parsifer provides tools to eliminate data leaks to third parties. The system uncovers bias before and after data processing, ensuring that your results are traceable, repeatable, and validated before you publish or submit claims. This increases trustworthiness in the system.
Public Sector: Government and Defense, indeed all government agencies have strict procurement rules addressing disclosure, specifically concerning the use of AI. In addition, the handling of classified information complicates data usage internally: Data leaks, poor data quality, insider misuse and theft.In order for data governance to be controlled, secure, and yet transparent to oversight bodies, the guards around access must be strong. The NIST AI Risk Management framework guides the backbone of Parsifer’s services, simplifying audits and liability management.
The Team
Sharon Bolding is an international business operations, product strategy and technical professional focusing on AI and Cybersecurity with a research background in natural language processing, machine learning, and data-driven product development. At Citibank Global, she led the team and implemented an AI platform for Compliance Surveillance, including a Risk Model in 42 languages. In 2024, she founded Parsifer to identify and track data usage within AI and profile risk. She has advised companies on growth strategies for products and emerging technologies in fintech, healthcare, cybersecurity, and AI. She has co-founded and sold four companies. She has been an adjunct professor and guest lecturer at the University of Washington and Seattle Pacific University. She received her BAs in French and German from the University of Washington (1986), an MA in French (1988), and her PhD. in Linguistics from University of British Columbia (1997).
Contact Us
All we need is 8 hours to understand and define the problem, then figure out a strategy before you spend a lot of money building an AI solution that might be misdirected. Technology is not always the answer. Sometimes it's process engineering or market fit. Honest advice and clear actionable plans for AI in your stack or project will result. Tell us about yourself and we'll meet up.
Boldingbroke Consulting is an LLC registered in the state of Wyoming. For more details, contact us.