FirmBrain Reasoning

Stateless reasoning for sensitive medical and legal data

A patented mechanism for efficient, stateless inference over protected records in healthcare and law. Built to increase oversight and efficiency in environments where traditional AI is difficult to deploy.

Currently piloting with healthcare, long term care and legal partners and exploring collaborations with cloud and hardware providers including GPU platforms.

What the system does

Reads a case or chart from zero, shows what is in the data, what does not align across records and what may be missing from the file or care pathway.

How it operates

Uses a stateless, non training mechanism so each run reconstructs reasoning fresh from the underlying records rather than storing or learning from PHI or PII.

Where it is aimed first

Medical legal work, personal injury cases and VerusHealth pilots in retirement and long term care settings focused on fall risk and missed steps in care.

FirmBrain

Reasoning over complex personal injury cases

FirmBrain was built inside a high volume personal injury practice to reason over thousands of resolved cases without training on client data. It connects medical records, legal documents and insurance details so teams can see the full story of a case and spot gaps before they turn into problems.

The same patented mechanism now powers a stateless inference layer that reads each case from zero. It focuses on alignment and absence rather than simple retrieval or summarization.

Designed to sit alongside existing case management systems, not replace them.

Cross document medical and legal alignment for injury cases
Highlights missing records, referrals and documentation early
Built from a large catalog of resolved personal injury cases
Stateless by design to respect client, patient and carrier data boundaries

VerusHealth

Oversight for long term and elder care

VerusHealth applies the same reasoning layer to healthcare operations. It looks across notes, orders, vitals, incident reports and communication records to surface care gaps, risk patterns and missed follow through.

The goal is simple. Help teams see the steps that should have happened but did not, while keeping sensitive medical information inside compliant environments.

Fall and risk workflows

Surfaces patterns around falls, near misses and risk factors across long time frames and multiple providers.

Missed steps in care

Flags when recommended referrals, follow up imaging or lab checks do not appear in the downstream record.

Family and caregiver visibility

Supports clear updates to families and caregivers while the system works in the background inside existing tools.

Technology

A patented, stateless inference layer

The mechanism focuses on efficiency and compliance aligned reasoning rather than training new models on sensitive data.

Stateless by design

Each run reconstructs its reasoning fresh from the underlying records. No training runs on PHI or PII and no persistent learned state tied to sensitive data.

Non training mechanism

The patented approach aligns information across documents and domains without building a long lived embedding index that becomes a new data asset to govern.

GPU ready workloads

Reasoning is decomposed into steps that can run in parallel and benefit from GPU acceleration at scale, especially in hospital, care center and legal settings with large case volumes.

Built for regulated environments

Designed to sit inside or alongside EHR, case management and claims systems so teams can add reasoning without changing their core system of record.

Where it helps first

Initial focus areas

Personal injury and medical legal work

Reads across medical records, imaging reports and legal documents to surface alignment issues and missing records in complex injury cases.

Retirement and long term care

Monitors long running charts, incidents and care plans to reduce missed steps in care, especially around falls and preventable complications.

Compliance and quality review

Supports internal review teams who need to see gaps and inconsistencies quickly without exporting sensitive data to external training systems.

About

Built from front line experience

FirmBrain Reasoning and VerusHealth were created by Dr Benjamin Greenwade, a doctor of chiropractic specializing in rehabilitation and complex medical documentation. He works daily with extensive medical records, personal injury cases and long term care needs.

The work began inside a high volume personal injury firm and expanded into a more general mechanism for reasoning over sensitive data without turning that data into model training material.

Dr Benjamin Greenwade

Founder, FirmBrain Reasoning and VerusHealth

A doctor of chiropractic with a focus on rehabilitation, functional assessment and complex medical legal documentation. Focused on building practical reasoning systems for law and medicine that respect real world constraints around privacy, regulation and clinical workflows.

Contact

Interested in partnering or learning more

For pilots, partnerships and technical discussions please reach out. We are especially interested in working with healthcare systems, long term care organizations, legal and insurance teams and cloud or hardware providers focused on regulated environments.

Email

ben@firmbrain.io

Please include a short note on your role and the type of environment you are working in so we can prepare relevant examples.