Deals
Most tools address only part of this journey. Search stops at finding. Review stops at insight. Remediation starts over in a new system. Each handoff introduces delay, inconsistency, and risk.
Thermal's Actionable Discovery approach treats this as one continuous evolution.
The deal requires separating buyer and seller IP before closing.
Can hundreds of millions of files be found and moved
across thousands of employees in time?
AI FOR DEALS TEAMS
What if closing deals on time and on budget didn't require all-nighters, weekends, or scrambling to stitch tools together?
Deal teams already know how to do the work. The strain comes from managing discovery, diligence, sensitive data review, and getting IP to the right side of the transaction across disconnected systems, tracked through spreadsheets and email.
The work gets done because people push hard. Thermal delivers a purpose-built end-to-end solution that lets teams move faster and stay on track, without constant heroics.
Real World Use Case
In a $2B divestiture, 5,000 employees were required to review 395 million files to determine which data remained with the seller and which transferred to a private equity buyer. The data separation effort relied on six tools, stretched a 60-day regulatory timeline to 10 months, and cost $3M. Thermal is designed to simplify data separations of this scale by consolidating discovery, review, and remediation into a single platform, allowing programs to conclude faster, with fewer people, at lower cost, and with higher margins for service providers.
Explore this Data Separation further →What Thermal Solves
Finding what matters is slow, manual, and often inaccurate.
Teams know the information exists, but not where it lives or which version matters. They search virtual data rooms, reopen files, and repeat the same checks across thousands or millions of documents. Time meant for judgment is spent reopening files as deadlines approach.
Web-based AI models weren't designed to process large volumes of files.
Web-based tools silently drop content as volumes grow. Teams get confident-sounding answers without clear visibility into what was included, what was missed, or whether the result can be defended later.
Turning insight into action requires stitching systems together.
Search happens in one tool. Review in another. Analysis somewhere else. Action in a fourth. Progress lives in spreadsheets and email. Time is spent coordinating technology instead of moving the deal forward.
How Deal Work Changes with Thermal
Thermal helps deal teams move from discovery through diligence, identify discrepancies and sensitive data, and take separation, preservation, or deletion when action is required.
Discovery — Find what matters
Teams start by narrowing massive data rooms into a defensible working set. Keyword and topic search is applied once, across all files, with results reviewed in context instead of reopening documents. Downstream work starts from a shared foundation of what matters.
Diligence — Make defensible decisions
With the right material curated, teams ask targeted questions, surface discrepancies, and complete diligence reports with every answer tied back to reviewed source files. Decisions are grounded in what was actually considered, not assumptions or incomplete inputs.
Classification — Identify sensitive data
Before data moves across organizational boundaries, sensitive personal, health, payment, or regulated information is identified across deal materials and broader digital assets. Teams gain visibility into exposure before systems are combined, not after.
Remediation — Take repeatable actions
Remediation is where decisions become durable outcomes, starting with preservation when required and carrying through to separation or mitigation through permanent deletion, so all copies of identified data end up in the right place before close.
Use Cases
- Buy-side and sell-side discovery and diligence
- Sensitive data classification and pre-integration health checks
- Sell-side data separation during TSA periods
- Buy-side CFIUS and ITAR data risk mitigation via deletion