You already know something
went wrong. I find out
exactly how.
Institutional forensics for legal teams, litigation finance firms, and legal tech companies that need analysis grounded in real court systems — not adjacent to them. Built on 12 years inside federal operations, tested in published investigations, proven in active Michigan litigation.
Most analysts have one vantage point. I have three — and I’ve published the proof.
Who I Work With
Organizations that cannot afford to be wrong about institutional risk.
Three tracks. One methodology.
Each track draws on the same core skill: building evidentiary records of institutional behavior that hold under scrutiny — primary sources, verifiable chains, publication-standard analysis.
What you get: a publication-standard evidentiary record of how a public institution, actor, or procurement network operates — built from primary sources and structured to hold in litigation or press.
I have mapped procurement networks, campaign finance flows, and intergovernmental accountability gaps at county and state level in Michigan and published the analysis. The Eaton County Drain Commissioner network (five law firms, MCL 280.247 anchors) is currently pre-publication. The Barry County investigation produced a Michigan Supreme Court remand. This is what the methodology delivers.
Best for: civil rights litigation teams · watchdog orgs · law firms · policy shops · campaigns · compliance teams.
- Document trail analysis & public records strategy
- Institutional network mapping
- Civil rights exposure assessment
- MMRMA / public insurer liability identification
- FOIA strategy, drafting & appeal support
- Campaign finance & procurement analysis
- Opposition research packages
- You have a pattern you can feel but can’t yet prove
- You need a public records strategy, not just a FOIA request
- You’re filing Section 1983 and need the institutional map first
- You need research that holds under cross-examination
- Your target is insulated inside bureaucratic structure
What you get: a structured analysis identifying whether a case, filing pattern, or institutional actor shows signatures of procedural abuse — and what the litigation risk or civil rights exposure looks like.
Procedural abuse follows identifiable signatures. I have documented them in active Michigan district court litigation and published the analysis. I have also been on the receiving end of these tactics — which means I know not just how to recognize them analytically, but how they are constructed filing by filing, designed to be invisible to attorneys who haven’t seen them before.
For litigation finance: this is the pre-investment screening layer that tells you whether a case walks into a jurisdiction where the deck is stacked. For insurance SIU: this is the pattern recognition infrastructure for identifying vexatious litigants before they escalate.
Best for: litigation finance firms · insurance SIU · legal ops departments · court reform organizations · plaintiff-side civil rights attorneys.
- Case file forensic review
- Procedural abuse signature identification
- Litigation risk pre-screening
- Bad-faith actor pattern analysis
- Pre-litigation institutional exposure assessment
- Vexatious litigant profile development
- Expert framing for legal reform advocacy
- You’re evaluating a case before committing capital
- The filing history looks unusual but you can’t name why
- You suspect pretextual enforcement but lack a documented pattern
- You’re building an early-warning system for process abuse
- You need a vexatious litigant profile that holds under scrutiny
What you get: a domain expert who has been inside a docket — not just adjacent to one — reviewing your product, workflow, or training data for gaps that only appear when your tool meets real court behavior.
Most legal AI companies have strong engineering teams and weak institutional depth. They know NLP. They don’t know how a clerk’s office actually processes filings, how a judge’s procedural quirks shape case outcomes, or how procedural abuse gets constructed filing by filing in ways that will never surface in clean training data. I do.
I build LLM workflows. I have published on AI ethics and institutional accountability. And I have 12 years managing data standards across 50+ federal agencies — which means I know where AI tools break against real institutional behavior, because I’ve been inside the institution.
Best for: legal AI startups & scaleups · e-discovery firms · court technology vendors · law school & research institutions.
- Court systems domain advisory
- LLM workflow development & implementation
- Product red-teaming for court-adjacent tools
- Training data quality & bias review
- AI ethics consultation
- Subject matter expert engagement
- Your product works in demos but attorneys push back in practice
- You need someone who can explain how courts actually work
- Your training data was built from clean records, not messy dockets
- You’re building for procedural edge cases and need someone who’s lived them
- You need a domain expert who can also build, not just advise
The problem this solves: your legal review says the merits are viable. But you don’t have a read on whether the jurisdiction, judge, or filing history introduces structural risk that will undermine an otherwise strong case.
This is a fixed-scope, fixed-price pre-investment screening engagement. I review the case file, analyze the procedural history and filing patterns, assess the jurisdictional context against documented patterns, map any public insurer (MMRMA) exposure, and deliver a written risk assessment with a clear viability read.
The output is a structured report you can use to make a funding or coverage decision — not a legal opinion, but a documented pattern analysis built to the same standard as Clutch Justice’s published investigations. Source documentation included.
Starting at $2,500 · Turnaround 5–10 business days · Retainer pricing available for pipeline screening.
- Procedural history & filing pattern analysis
- Jurisdictional & judicial context assessment
- Procedural abuse signature identification (if present)
- Public insurer / MMRMA exposure mapping
- Bad-faith actor flag (if applicable)
- Written risk assessment with viability read
- Source documentation appendix
- You’re evaluating a case before committing capital or coverage
- The legal merits are solid but the procedural record is murky
- You’ve been burned by jurisdiction risk you didn’t see coming
- You want a second-layer screen legal review alone doesn’t provide
- You have a pipeline and need a fast, repeatable process
Active investigations. Published frameworks. Verifiable in the public record.
These are not case studies constructed for a portfolio. They are active and published investigations demonstrating the methodology in real time — before institutions acted, not after.
Michigan courts operate on a binary model: a judge is either licensed or removed. No mechanism exists for early detection, temporary relief, or structured transition when capacity declines. The Fit-Bench Act proposes a three-layer confidential assessment system — baseline evaluation at entry, monthly performance data capture, and triggered confidential review when statistical thresholds are crossed.
This is what the forensics-to-policy pipeline looks like in practice. Draft statutory language, a functional web-based scorecard application, and briefing materials are available on request.
Enterprise engagement models.
All four models are available for immediate engagement across all three service tracks. Project-based and retained advisory work can begin within days of agreement.
Your case isn’t adding up. Start here.
If you are an individual, a family member, or a smaller organization dealing with a matter where the record is fragmented, the timeline doesn’t hold together, or you feel like the system isn’t being straight with you — these are the entry points. All are paid. All begin with structure, not opinions.
Rita F. Williams
“I am not an outside observer of institutional dysfunction. I have been inside a federal agency, district court proceedings, and an investigative desk — and came out with receipts. That vantage point is what I sell.”
- SQL · Python · Data modeling
- LLM workflow development
- EDI/X12 standards
- WordPress · Agile/Scrum
- SharePoint · Microsoft Access
- Secret Security Clearance
- Lapsed · Reactivatable
Before you reach out.
No free previews. No informal reads. No quick assessments via email or DM. All engagements begin at the intake form. All inquiries are confidential.
The record doesn’t lie.
Let’s read it together.
Project-based, retained advisory, expert framing, or speaking. Available for immediate engagement across all three service tracks. Response within one business day.