Skilak KeepRequest a pilot

Industries

For work that must stay inside.

Keep gives teams a practical path to AI where business-sensitive, proprietary, regulated, or controlled context must remain within a customer-governed environment.

Operating environments

Private infrastructure. Domain-specific value.

The system is the foundation. The business outcome comes from choosing a bounded workflow, approved knowledge, named users, and measurable acceptance criteria.

Government contractors

Sensitive business context, no public model

Support capture, proposal development, policy research, and internal knowledge discovery within a customer-governed enclave.

  • RFP and requirement analysis
  • Past-performance discovery
  • Controlled proposal assistance

Healthcare and clinical operations

AI near patient records, not at a vendor

Self-hosting means no external model provider receives a patient record, which takes the vendor business-associate question off the table. The access control, audit logging, and encryption obligations stay with you; the system is built to be evidenced against them, not to discharge them.

  • Clinical policy and procedure search
  • Prior-authorization and documentation support
  • Research and quality-review synthesis

Legal and privileged work

Client material stays inside the firm

Privileged and confidential matter content never reaches a public model, because there is no outbound path for it to take. Retrieval is scoped to the collections a matter team is permitted to see, and answers cite the source document.

  • Matter and precedent research
  • Discovery and document review support
  • Template and prior-work reuse

Regulated operations

AI for controlled records and procedures

Give approved staff a faster way to find and synthesize information while preserving the organization's identity, network, and retention controls.

  • Policy Q&A
  • Procedure search
  • Evidence-backed summaries

Engineering & manufacturing

Technical knowledge close to the work

Search specifications, manuals, quality records, and engineering notes from a system placed inside the operating environment.

  • Technical document retrieval
  • Maintenance support
  • Controlled knowledge transfer

Professional services

Institutional knowledge as a private tool

Help teams reuse approved methods, templates, research, and deliverables without sending client material to a public AI service.

  • Matter and project research
  • Template discovery
  • Internal drafting support

Government contractors

A worked example: the proposal shop.

A mid-sized GovCon firm can begin with a focused group, often capture, proposals, contracts, or engineering, then expand only after the first workflow is useful, governed, and supportable.

Plan a GovCon briefing

Capture and proposal operations

Analyze requirements, find relevant past performance, compare approved source material, and support structured drafting without sending proprietary context to a public model.

Policy and contract knowledge

Give authorized teams a citation-backed way to navigate internal policy, contract references, process guidance, and approved research collections.

Engineering and program context

Help technical staff locate approved specifications, decisions, procedures, and lessons learned across a controlled knowledge base.

Choose the first workflow

A strong candidate has a boundary and a reviewer.

  1. The workflow depends on information the organization is permitted to use.

  2. A reviewer can define what a good answer looks like and check citations or output quality.

  3. The process is frequent or costly enough that faster retrieval or synthesis matters.

  4. The organization can name the users, data owner, system owner, and approval authority.

Compliance posture

Infrastructure supports a program. It does not replace one.

Keep is designed to fit within a customer's CMMC, HIPAA, ITAR, or other security program. Skilak does not certify or confer compliance.

Pilot

Bring one bounded workflow. Leave with a deployment shape.

We will help separate what the AI should do, what data it may use, who may access it, and what the system must prove before go-live.