AI that works where your information cannot leave.
SolveWorks builds local, on-premise, and client-controlled AI agents for legal, healthcare, finance, HR, insurance, and other sensitive operations — with approval gates, audit trails, and a clear rule: raw client data stays in your environment.
Client-controlled route
No raw data to our cloud
Sensitive source systems
Documents, client records, transcripts, CRM notes, policies, intake forms, and internal SOPs.
Local/private agent runtime
Runs on dedicated Mac hardware, a private server, or approved on-premise environment.
Redacted escalation only
Cloud/frontier models are optional and only receive minimized, approved context when the workflow allows it.
Human approval and receipt
Drafts, summaries, updates, and recommendations stay approval-gated with an audit trail.
Compliance note: SolveWorks designs privacy-first AI infrastructure and workflow controls. Formal regulatory compliance obligations remain scoped per client, policy, counsel, and system environment.
Built for work with real confidentiality risk.
These are the workflows where a generic cloud chatbot is not enough.
Legal and professional services
Matter summaries, discovery organization, intake prep, contract extraction, and client communication drafts without exposing raw case files by default.
Healthcare and clinics
Policy Q&A, admin summaries, referral workflows, patient-service triage, and documentation support with client-controlled data handling.
Finance and insurance
Client file review, renewal prep, risk notes, portfolio/admin summaries, and internal assistant workflows for sensitive financial records.
HR and recruiting
Candidate packets, hiring notes, internal policies, compensation-sensitive material, and interview summaries with local/private processing options.
Security-sensitive operations
Airgapped or low-connectivity workflows, private research, board materials, M&A prep, and executive operations where leakage risk matters.
Document-heavy teams
Thousands of files become searchable, summarized, and action-ready while source documents remain inside the approved environment.
The service
Private AI Agent Buildout
We design the full operating layer: hardware or private hosting, model routing, local tools, source permissions, approval gates, recovery plans, and receipts. The agent can still use frontier cloud models when allowed — but sensitive workflows get a local/private lane.
Map my private AI workflow →1. Data boundary map
Which data can be local-only, redacted, cloud-eligible, or human-only.
2. Local model lane
Routine classification, extraction, summaries, redaction, and drafts run on client-controlled infrastructure.
3. Approval ladder
Read-only, draft-only, approval-gated actions, then bounded automation only when proven safe.
4. Audit receipts
Every important action leaves source references, routing decisions, confidence notes, and human approvals.
5. Cloud fallback rules
If cloud is allowed, the agent escalates only with minimal approved context and logs the reason.
6. Continuity plan
Provider outage, auth failure, and rate-limit modes so the business can keep operating.
The result: useful AI without the usual data tradeoff.
Your team gets the speed of AI workflows while keeping sensitive source material under client control. Start with one high-value workflow, prove it in read-only/draft mode, then expand permission only after the system earns trust.
Process sensitive data inside your approved environment.
Escalate hard tasks with redacted/minimized context.
Logs, approvals, and receipts for operator confidence.
Want to know what can safely run private?
Book a private AI audit. We will map one sensitive workflow, identify what should stay local, what can use cloud, and what must remain human-approved.