Bench IQ is an AI-powered judicial intelligence platform for litigators, focused on helping attorneys understand how specific judges think and rule. Public evidence consistently describes the product as going beyond published opinions by analyzing broader judicial data to surface patterns in judges’ reasoning, motion tendencies, and likely decision paths. The company was founded in 2023 by ROSS Intelligence alumni and former Kirkland & Ellis partner Jeffrey Gettleman. Public funding coverage shows a $2.1M round in 2024 and a $5.3M seed round announced on August 27, 2025, implying at least $7.4M raised if those rounds are cumulative. Coverage from PR Newswire, BusinessWire, LawNext, Reuters, BetaKit, Battery, and Inovia positions Bench IQ as an emerging litigation-research vendor with early BigLaw traction, but public pricing, review-platform coverage, and security disclosure remain thin.
Company Info
- Founded: 2023
- Team size: 1-10 employees
- Funding: $2.1M
- HQ: United States
- Sector: Litigation
What We Haven’t Verified
This page was assembled from publicly available information. Feature claims and workflow mappings are based on what the vendor and third-party listings publish — not hands-on testing or practitioner feedback.
Workflows
Based on practitioner evidence, Bench Iq is used in these workflows:
What practitioners struggle with
Real frustrations from legal professionals — the problems Bench Iq addresses (or should address). Sourced from practitioner reviews, Reddit threads, and case studies.
Litigation firm needs to build custom analytics dashboards — track motion success rates by judge, venue, and case type across state and federal courts — but existing tools offer pre-built reports that don't match their specific strategic questions
Litigation team preparing for trial needs to understand how a specific judge rules on summary judgment motions, Daubert challenges, and sentencing — but there's no systematic analytics on judge behavior, so strategy relies on anecdotes from colleagues who've appeared before that judge
Litigation associate researching how Judge X handles class certification, summary judgment, or a Daubert motion only sees the small slice of rulings that become published opinions — the rest of the judge's reasoning is buried in transcripts and non-opinion rulings, so case strategy depends on hallway gossip and lawyers' memory instead of systematic evidence
Where it fits in your workflow
Before Bench Iq
Litigator receives judge assignment or prepares a major motion/trial strategy -> team needs to know how this judge has ruled on similar issues, what reasoning patterns recur, and where conventional case-law research leaves blind spots
After Bench Iq
Bench IQ generates judge-focused intelligence from a proprietary judicial dataset -> litigation team uses the output to refine motion strategy, oral argument themes, venue assessment, and pitch materials -> firm knowledge compounds around judge-specific strategy rather than anecdote
Integrations & hand-offs
Court dockets, transcripts, and judicial data -> Bench IQ analysis layer -> litigation partner/associate/knowledge team -> briefing, strategy, and client-facing litigation planning
Also used by similar teams
Community Data
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