What becomes possible when the data never leaves.
Most organizations in regulated industries have made the same quiet calculation. The AI tools everyone else uses are off limits, because the data that matters most, privileged files, patient records, controlled information, customer and deal data, cannot be sent to a public cloud. So the work stays manual, and the capability stays out of reach.
Feerstone removes that constraint. Every use case below runs on hardware you own or on private infrastructure under your control, inside your jurisdiction. Nothing is sent to a public model. The point is not novelty. The point is that you can finally apply this capability to the material it was always meant for, without breaking a single obligation you carry.
The page is organized by industry. Find yours, and read past the obvious items. The work most firms underuse is rarely the work they came looking for.
Legal
For law firms and in-house legal teams, the governing concern is privilege. Anything that touches the matter file has to stay inside the firm. These capabilities are delivered through ClerkBox, our private legal retrieval and drafting system.
Search the entire matter archive.
Ask plain-language questions across decades of pleadings, memoranda, contracts, and correspondence, and get answers grounded in the firm's own work. The associate hour spent hunting for the right precedent becomes a query, and the precedent never leaves the building.
Draft from your own precedents.
Generate first drafts of briefs, motions, and agreements built on the firm's actual prior filings, not a public model's approximation of how such a document should read. The output sounds like the firm because it is trained on the firm.
Review documents at production scale.
Surface relevant material, flag likely privilege, and extract key facts across large document sets, all on private hardware. This is document review and early case assessment without handing the production to an outside vendor's cloud.
Extract obligations from contracts.
Pull dates, renewal and termination triggers, indemnities, and unusual clauses across a contract portfolio, so nothing material is buried in a file no one has opened in two years.
Analyze transcripts and depositions.
Search testimony, summarize long transcripts, and find contradictions across sessions in minutes rather than days.
Triage intake and check conflicts.
Structure incoming matters and test them against the firm's history before a conflict becomes a problem.
Capture knowledge before a partner retires.
A senior partner's judgment is mostly undocumented. A private assistant trained on their files and memos preserves a usable version of that knowledge after they leave.
Handle bilingual and Quebec matters in place.
Work across French and English files without sending privileged material to a third-party translation service, which matters both for confidentiality and for Law 25.
Clean up billing narratives.
Draft consistent, defensible time entries from rough notes, which improves realization without adding administrative load.
Healthcare
For hospitals, clinics, and health systems, the constraint is the protection of health information under HIPAA in the United States and PHIPA in Ontario. Patient data cannot transit a third party. These capabilities are delivered through ScribeStation, our on-premise clinical capture and documentation system.
Document the encounter as it happens.
Capture the clinical conversation and draft the note in the background, on the client's own hardware, so protected health information never leaves the perimeter. The result is less time in the record and more time with the patient, which is the single most reliable lever against clinician burnout.
Search the longitudinal record.
Ask questions across a patient's full history and get a grounded answer, rather than scrolling through years of entries to reconstruct a picture.
Draft discharge summaries and referral letters.
Produce a clean first draft directly from the chart, ready for clinician review and sign-off.
Support coding and prior authorization.
Suggest the likely codes from the encounter and assemble the documentation a prior authorization or claim requires, reducing denials and rework.
Draft patient communication.
Prepare messages and instructions in the clinician's voice, always reviewed before anything is sent.
Identify research cohorts without exporting data.
Find patients who meet study criteria across the record while the data stays inside the institution.
Prepare quality and regulatory submissions.
Draft the required reporting and audit material from existing records, which is some of the most disliked and time-consuming work in any health system.
Serve multilingual patient populations on-premise.
Generate intake material and instructions in a patient's own language without routing health data through an outside translation tool.
Summarize nursing handoffs.
Produce a reliable shift-change summary from the record, where missed detail carries real clinical risk.
Retire transcription vendors.
Bringing dictation and documentation in-house removes both a recurring cost and a standing third-party data-handling risk.
Defense and Government
For defense industrial base contractors, the constraint is the handling of Controlled Unclassified Information under CMMC and NIST 800-171. Information cannot leave the certified boundary. These capabilities are delivered through CMMC-Ready RAG, architected to operate inside a CMMC Level 2 enclave.
Make controlled documents searchable inside the boundary.
Search and summarize CUI without it ever crossing the enclave perimeter, so the capability and the compliance posture hold at the same time.
Support capture and proposals.
Draft responses to solicitations grounded in the contractor's own past performance and technical history, entirely in-enclave, which shortens the proposal cycle that small contractors most often lose on time.
Assemble compliance evidence.
Help build and maintain the System Security Plan and supporting documentation, and map implemented controls against the required practices, so an assessment finds an organized record rather than a scramble.
Generate technical documentation.
Produce drafts from engineering specifications and existing artifacts, keeping regulated technical data on controlled infrastructure.
Analyze contracts and clauses.
Work through FAR and DFARS clauses and flow-down obligations without leaving the boundary.
Track subcontractor flow-downs.
Keep a current, queryable view of which requirements pass to which subcontractors, where a single missed flow-down can put a prime contract at risk.
Onboard cleared personnel faster.
A private knowledge base built on internal procedures shortens the time a new cleared hire takes to become useful.
For public sector buyers: process records and FOIA-style requests, manage records retention, and draft policy material, all on government-controlled infrastructure, which is the only way most of this work can be done with AI at all.
Financial Services
For banks, credit unions, insurers, and investment firms, the constraints are model risk and third-party risk under guidance such as OSFI E-23 and B-13, alongside data residency expectations. Customer and deal data has to stay where it belongs. These capabilities are delivered through private deployment paired with our Cross-Border Compliance Advisory.
Support model risk documentation and validation.
Draft and review model documentation, check it for internal consistency, and map it against the institution's model risk obligations, on infrastructure that keeps the underlying data in place.
Map regulatory change to your own policies.
When new guidance lands, identify which internal policies and controls it touches and where the gaps are, rather than rereading the entire policy library by hand.
Draft credit memoranda and underwriting analysis.
Produce structured first drafts from internal data, leaving the analyst to judge rather than to assemble.
Support KYC and AML investigations.
Summarize case files and surface patterns across a customer's history while the data stays inside the institution.
Analyze loan documents and agreements.
Work through facility agreements, ISDAs, and security documents to extract terms, obligations, and anomalies.
Assemble audit and control evidence.
Pull together the documentation internal audit and control testing require, from records that never leave the environment.
For wealth, private equity, and private credit.
Review deal data rooms, draft investment committee memoranda, and prepare investor reporting, all on private infrastructure, which is the only deployment that respects the confidentiality of a live deal.
Draft complaint handling and regulatory reporting.
Turn raw case detail into the consistent, defensible reporting regulators expect.
Run cross-border data residency reviews.
Establish where data sits and under whose jurisdiction it falls when a system processes it, which is the question a regulator asks first and most institutions answer poorly.
Process third-party risk questionnaires.
Handle inbound and outbound vendor risk assessments, which are high volume and rarely staffed well.
Operate bilingually.
Manage French-language regulatory and client material in place, without exporting it.
Accounting and Professional Services
For audit, tax, and advisory firms, client data carries a duty of confidentiality, and the work is seasonal and document-heavy. Private deployment lets these firms apply AI to client files without breaching that duty.
Support working paper review.
Help tie out and review working papers, flagging inconsistencies for a human to resolve.
Ground tax research in your own positions.
Research questions against the firm's prior positions and the client's own files, rather than a generic source that knows neither.
Draft engagement letters and reports.
Produce first drafts from the firm's templates and the engagement record.
Classify and route client documents.
Sort and organize inbound client material so the team starts from order rather than a shared drive.
The work that compounds quietly.
Capturing the institutional knowledge that walks out at partner retirement, handling bilingual client files, and absorbing busy-season volume without proportional headcount.
Pharmaceuticals and Biotech
For drug developers and biotech firms, two kinds of data cannot move freely. The trial data is protected health information, and the compound, formulation, and process work is the company's entire value. Regulators expect controlled, validated records under FDA 21 CFR Part 11, Health Canada, and the GxP standards, and proprietary research is a trade secret the moment it exists. Public-cloud AI is incompatible with both.
Search the research record.
Ask questions across decades of lab notebooks, study reports, and internal research without any of it leaving the company. Knowledge currently locked in documents and in the heads of senior scientists becomes usable.
Draft regulatory submissions.
Assemble and draft the documents behind a marketing authorization or new-drug application, grounded in the company's own study data, on validated and controlled infrastructure.
Process pharmacovigilance data.
Read, code, and summarize adverse-event and safety reports at volume, where the data is both protected and tightly regulated.
Review clinical documentation.
Work across protocols, clinical study reports, and investigator material to answer questions and find inconsistencies before a regulator does.
Support GMP batch-record review.
Surface deviations and anomalies in manufacturing records held on controlled systems.
Combine private and public literature.
Run literature review across the company's internal corpus and external sources together, without exposing the internal half.
Inspection and audit readiness.
Assemble the record an FDA or Health Canada inspection will demand, and rehearse the likely questions, from documentation that never leaves the firm.
Capture departing-scientist knowledge.
A retiring principal investigator's judgment is mostly undocumented. A private assistant trained on their work preserves a usable version of it.
Multilingual global-trial documents.
Handled in place rather than sent to an outside translation service.
Formulation and process IP.
Kept queryable internally while never touching a third-party model.
Insurance
Insurers hold two regulated data types at once: the health information in claims and the personal and financial information in policies. Health claims fall under HIPAA in the United States and provincial health-privacy law in Canada, customer data is governed by privacy law on both sides of the border, and underwriting and pricing models face growing scrutiny for fairness. None of this can be handed to a public AI service.
Support claims adjudication.
Read and summarize medical records and claim files, extract the facts a decision turns on, and flag inconsistencies, all on infrastructure the data never leaves.
Assist underwriting.
Pull the relevant detail from applications and supporting documents into a structured view, leaving the underwriter to judge rather than to assemble.
Analyze policy documents.
Work across policy wordings, endorsements, and contracts to answer coverage questions and surface anomalies.
Support fraud investigation.
Summarize case files and surface patterns across a claimant's history while the data stays in place.
Draft correspondence and filings.
Prepare decision letters, coverage explanations, and regulatory submissions in the company's voice, always reviewed before sending.
Review subrogation files.
Identify recovery opportunities buried in closed files.
Document pricing and underwriting models for fairness review.
As regulators press on discriminatory outcomes, defensible model documentation becomes a requirement, not a nicety.
Complaint reporting.
Turn raw complaint detail into the consistent record regulators expect.
Multilingual policyholders.
Served in place without exporting their data.
Catastrophe-claim surges.
Absorbed without a proportional rise in headcount.
Energy and Utilities
For utilities and energy operators, the constraint is critical-infrastructure security. Operational technology, grid data, and control-system documentation are governed by standards such as NERC CIP, and much of it is deliberately kept off any public network. The AI that would help run and maintain the system has to live inside the same protected boundary as the system itself.
Search operations and maintenance documentation.
Put decades of manuals, procedures, and asset records behind a single query, available in the control room without anything leaving the protected environment.
Assemble NERC CIP compliance evidence.
Help build and maintain the documentation an audit requires, mapped to the relevant requirements.
Analyze outages and incidents.
Work across logs and reports to reconstruct what happened and what to change, while sensitive operational data stays in place.
Retrieve emergency and restoration procedures.
Give field and control-room staff fast, reliable access to the right procedure under pressure.
Review vendor and third-party risk.
Process the supplier assessments that critical-infrastructure operators are expected to perform.
Support regulatory and environmental filings.
Drafted from internal records.
Capture retiring-operator knowledge.
The people who know how a specific plant or grid segment actually behaves are retiring, and that knowledge should be captured before it leaves.
Field crews in low-connectivity conditions.
Served by an on-device assistant that works at a remote site with no network and no exposure.
Environmental compliance reporting.
Drawn from monitoring data held internally.
Interconnection and permitting documents.
Which are voluminous and slow.
Advanced Manufacturing, Semiconductor, and Aerospace
In advanced manufacturing, semiconductors, and aerospace, the crown jewels are process recipes, designs, and the accumulated judgment of process engineers. Much of this is export-controlled under ITAR or the EAR, and almost all of it is trade-secret material that cannot reach a foreign competitor through a public model. The cross-border Windsor and Detroit corridor concentrates exactly these firms.
Build a process and recipe knowledge base.
Make hard-won process knowledge searchable on controlled infrastructure, so it is available to the next shift but never to anyone outside the company.
Search designs and drawings.
Query CAD and engineering documentation to find the right revision, the relevant tolerance, or the prior solution to a recurring problem.
Analyze quality and nonconformance data.
Surface the patterns behind defects and yield loss across production records.
Handle export-controlled technical data.
Keep ITAR and EAR flagged material on controlled systems while still making it usable to authorized staff.
Run a quote and proposal engine.
Drafting responses grounded in the firm's own past work and capabilities.
Search equipment manuals and maintenance history.
To shorten downtime.
Capture process-engineer tribal knowledge before retirement.
Which in this sector is often the single largest unrecorded asset.
Export-control classification assistance.
A task that is tedious, high-stakes, and poorly staffed at most firms.
Multilingual global plants.
Operated without moving sensitive technical data between them.
Traceability and first-article documentation.
That customers and auditors demand.
Mining and Natural Resources
For mining and resource companies, exploration and reserve data is both proprietary and price-sensitive, sites are remote and security-conscious, and disclosure is regulated. Technical reporting standards such as NI 43-101 in Canada govern what may be said about a deposit. AI that touches this data has to respect both the commercial sensitivity and the disclosure rules, which rules out public services.
Search geological and exploration data.
Make decades of drilling, assay, and survey data queryable internally, without exposing material non-public information.
Draft technical reports.
Assemble and draft the documentation behind a regulated resource disclosure from the company's own data.
Handle environmental and permitting documentation.
Working across the large, slow-moving document sets that permitting requires.
Retrieve health and safety procedures.
Give remote-site crews fast access to the right procedure, on a device that works without connectivity.
Analyze equipment maintenance and reliability records.
To reduce downtime at remote operations.
Review contracts and supplier agreements.
For obligations and risk.
Treat reserve and exploration data as material non-public information.
And keep it off any system that could leak it ahead of disclosure.
Capture the knowledge of senior geologists and mine engineers.
Before they retire.
Incident and safety reporting from the field.
Consolidated and queryable across sites.
Land, claims, and community-agreement records.
That are easy to lose track of.
Education
Schools, colleges, and universities hold student records protected by FERPA in the United States and provincial access-and-privacy law in Canada, campus health data under health-privacy rules, and research data that often carries its own sovereignty conditions. For institutions with foreign research partners, where that data sits is a live question. Public-cloud AI does not fit any of these.
Search student and institutional records safely.
Answer administrative questions across protected records without the data leaving the institution.
Process admissions and enrolment documents.
Reading, classifying, and routing high volumes of application material.
Keep research data on-premise.
Give researchers AI over their own datasets without exporting data that may be bound by sovereignty or partner conditions.
Build an institutional knowledge base.
Make policies, procedures, and accumulated administrative knowledge available to staff through a single private assistant.
Triage information requests.
Processing freedom-of-information requests against institutional records.
Draft grant proposals.
Grounded in the institution's prior successful applications.
Protect the data of minors in K-12 settings.
Where the privacy bar is highest and the tolerance for error is lowest.
Accreditation and program review.
Which demand large evidence assemblies on a cycle.
Multilingual students and families.
Served in place without exporting personal data.
Research involving foreign co-investigators.
Where data residency is the governing concern.
Telecommunications
Telecom operators hold customer proprietary network information and subscriber data under specific rules, CPNI in the United States and CRTC requirements in Canada. They handle sensitive lawful-access requests, and their network topology is itself security-sensitive. This is regulated, critical-infrastructure data that cannot be processed on a public AI service.
Support customer operations within CPNI limits.
Summarize and answer questions across account and service records while respecting the rules that govern that data.
Search network operations documentation.
Make configuration, procedure, and topology documentation queryable internally without exposing it.
Draft regulatory filings.
Prepared for the relevant regulator from internal records.
Analyze contracts and interconnection agreements.
For terms and obligations.
Support fraud investigation.
Across account and usage data held in place.
Equip field technicians.
With a private knowledge base of procedures and equipment documentation.
Handle lawful-access and legal requests consistently.
Where accuracy and auditability matter most.
Keep network topology documentation off any public system.
While still making it usable to engineers.
Capture the knowledge of senior network engineers.
Before they leave.
Serve a multilingual subscriber base.
Without exporting subscriber data.
Government Contractors
Government contractors live or die on two things: winning bids and protecting controlled information. Federal contract information and controlled unclassified information carry handling obligations under FAR, DFARS, and the NIST 800-171 family, and Canadian federal work carries its own requirements. For defense-specific programs, see also Defense and Government. The information involved cannot be processed on a public AI service.
Support capture and proposals.
Draft responses to solicitations grounded in the contractor's own past performance and proposal library, entirely on controlled infrastructure, which directly attacks the deadline pressure small contractors most often lose on.
Build a past-performance knowledge base.
Make every prior contract, deliverable, and lesson learned queryable, so the next bid starts from the firm's real history.
Provide controlled-information document intelligence.
Search and summarize federal contract information and controlled unclassified information inside the boundary that protects it.
Assemble compliance evidence.
Building and maintaining the documentation that demonstrates the controls a contract requires.
Analyze contracts and clauses.
Working through FAR and DFARS provisions and flow-down obligations without leaving the boundary.
Support bid and no-bid analysis.
From the firm's own win and loss record.
Track subcontractor flow-downs.
Where a single missed requirement can put a prime contract at risk.
Capture the knowledge of a departing capture manager.
Often a firm's most valuable and least documented asset.
Bilingual requirements for Canadian federal work.
Handled in place.
The cross-border case, handled directly.
A contractor serving both Canadian and United States government customers can keep each side's data in the correct jurisdiction under one roof.
Applies to Any Regulated Firm
Some of the most valuable work has nothing to do with a specific industry. These capabilities apply to any organization that holds information it cannot expose, and they are where most firms find the use they did not know to ask for.
Ask your own documents.
A private assistant that answers questions across everything the organization knows, its policies, contracts, prior work, and correspondence, without any of it leaving the building. For many firms this single capability justifies the engagement.
Triage and draft from the inbox.
Sort incoming mail, surface what needs attention, and prepare drafts for review, on private infrastructure rather than a consumer email assistant that reads everything.
Prepare board packs and briefings.
Assemble and summarize the material a board or committee needs, in the format they expect, from internal sources.
Track obligations and renewals.
Maintain a queryable view of contractual obligations, key dates, and renewal and termination windows across the whole organization.
Monitor regulatory change against your policies.
Watch for relevant change and map it to the specific internal documents it affects, so nothing is missed and nothing is reviewed twice.
Build an onboarding and training assistant.
Stand up a private assistant on internal procedures so new staff can ask questions instead of interrupting colleagues.
Automate redaction and data minimization.
Identify and mask sensitive information at scale, which is tedious, error-prone, and exactly the kind of work that should never be sent to an outside tool.
Review due diligence material.
Work through data rooms for transactions and vendor reviews, extracting the facts and flags that matter, with the material held privately throughout.
Capture meetings and produce minutes.
Record and summarize internal meetings on private infrastructure, where the discussion is too sensitive for a public transcription service.
Operate across languages in place.
Handle French and English material for bilingual Canadian operations without exporting anything, which keeps both confidentiality and Law 25 obligations intact.
For law firms and in-house legal teams, the governing concern is privilege. Anything that touches the matter file has to stay inside the firm. These capabilities are delivered through ClerkBox, our private legal retrieval and drafting system.
Search the entire matter archive.
Ask plain-language questions across decades of pleadings, memoranda, contracts, and correspondence, and get answers grounded in the firm's own work. The associate hour spent hunting for the right precedent becomes a query, and the precedent never leaves the building.
Draft from your own precedents.
Generate first drafts of briefs, motions, and agreements built on the firm's actual prior filings, not a public model's approximation of how such a document should read. The output sounds like the firm because it is trained on the firm.
Review documents at production scale.
Surface relevant material, flag likely privilege, and extract key facts across large document sets, all on private hardware. This is document review and early case assessment without handing the production to an outside vendor's cloud.
Extract obligations from contracts.
Pull dates, renewal and termination triggers, indemnities, and unusual clauses across a contract portfolio, so nothing material is buried in a file no one has opened in two years.
Analyze transcripts and depositions.
Search testimony, summarize long transcripts, and find contradictions across sessions in minutes rather than days.
Triage intake and check conflicts.
Structure incoming matters and test them against the firm's history before a conflict becomes a problem.
Capture knowledge before a partner retires.
A senior partner's judgment is mostly undocumented. A private assistant trained on their files and memos preserves a usable version of that knowledge after they leave.
Handle bilingual and Quebec matters in place.
Work across French and English files without sending privileged material to a third-party translation service, which matters both for confidentiality and for Law 25.
Clean up billing narratives.
Draft consistent, defensible time entries from rough notes, which improves realization without adding administrative load.
Every capability on this page is deployed on infrastructure you own or control, inside the jurisdiction you require. We do not send your material to a public model, we do not resell anyone's products, and we do not keep a copy of your data. We design the system, install it, and maintain it. The work stays yours.
Start with one high-value use case. Prove it. Expand from there.
You do not need to adopt all of this at once, and you should not. Most engagements start with a single high-value use case, prove it inside your own environment, and expand from there. If something on this page resembles a problem you carry, we would welcome a confidential conversation about it.