System Overview
SkyPath Privata is a private AI application designed to help teams work faster on RFIs, RFPs, proposals, and related opportunity content while keeping data handling controlled and confidential. The platform combines stateless AI processing with document retrieval so users can generate answers, proposals, summaries, presentations, images, and supporting business content without depending on public AI systems.
At a high level, the system is built for organizations that need modern AI workflows together with stronger privacy, governance, and operational control. This makes it especially useful for teams working with sensitive customer information, regulated content, or internal knowledge that should not be exposed to public AI tools.
INFO
SkyPath Privata uses stateless AI workflows and collection-based retrieval. Prompts are processed per request, and supporting context is supplied from the documents and websites you control inside the platform.
Platform Purpose
The primary purpose of the system is to accelerate document-driven response work. Instead of manually reading large source documents, finding supporting material, drafting responses, and formatting output by hand, users can organize an opportunity inside the platform and use AI tools to produce working drafts faster.
The system is designed to support:
- RFI response generation
- RFP and proposal drafting
- Document summarization
- Secure AI chat against private document context
- Search across uploaded document collections
- Creation of supporting collateral such as presentations, profiles, and images
Core System Components
The platform is organized around a few main concepts that work together.
Accounts and Access
Users register with either an Individual or Corporate account and sign in using email and SMS verification. Individual accounts are intended for single-user workflows, while Corporate accounts are intended for team-based work and controlled collaboration.
Projects
Projects are the main workspace for a sales activity, bid, contract response, or proposal effort. A project groups the source documents, instructions, collections, and AI-generated output for one opportunity so work stays organized in one place.
Source Documents
Source documents are the primary RFI or RFP files that need to be answered. These are uploaded to a project and then processed using either the Q&A Method or the Proposal Method.
Knowledgebase and Collections
The Knowledgebase is the document library that supports AI generation. Its contents are organized into collections, which group related documents and websites such as product guides, company background documents, pricing tables, previous responses, statements of work, and technical references.
Collections are attached to projects so the AI tools use the right supporting context for a specific opportunity.
Instructions
Projects include an instructions area that stores special responder guidance. Instructions can be entered manually or extracted from the source document. These instructions help the AI tools follow formatting requirements, word limits, customer requests, and other constraints.
Standard User Workflow
The typical workflow inside the system follows a repeatable pattern:
- Create a project.
- Upload the main source document.
- Choose the processing method.
- Attach or build the supporting collections.
- Review or extract project instructions.
- Generate answers, proposals, or other supporting content.
- Edit the output in the rich text editor.
- Download the final deliverable in the required format.
This workflow can be done manually or through the Project Wizard, which guides the user through project setup, Knowledgebase selection, and document processing.
Response Processing Modes
The system supports two main response modes for source documents.
Q&A Method
The Q&A Method is used when a source document contains separate questions, requirements, or response items that should each be answered individually. The system extracts likely response items, numbers them, and prepares them for answer generation and later export.
Proposal Method
The Proposal Method is used when the source document should be evaluated as a whole. Instead of answering each item separately, the system generates a single consolidated narrative response describing the overall solution.
TIP
Use Q&A when the final deliverable should preserve question-by-question responses. Use Proposal when the final deliverable should read like one complete solution document.
AI Tools in the Platform
In addition to the main RFI and RFP response workflows, the platform includes a broader set of AI tools available through projects or the Quick Actions toolbar.
These tools include:
- AI-powered question extraction
- AI-powered answer generation
- Presentation generator
- Image generator
- Document summarization
- Document content search
- Profile and background generator
- Secure chat
- SAM.gov public bid search
These tools allow users to move beyond the core response workflow and generate the supporting materials often needed around an opportunity.
Secure Chat and Ad Hoc Work
Secure Chat provides a conversational interface for users who need quick answers, short drafts, or document-aware responses without starting a full response workflow. Users can include collections in chat so the system answers with private Knowledgebase context.
This is useful for:
- Testing likely answers before using them in an RFI response
- Drafting emails or short opportunity content
- Querying product or service details from uploaded collections
- Exploring technical, operational, or infrastructure information conversationally
Privacy and Data Handling Model
The platform is designed around a privacy-first model.
- AI model calls are stateless
- Prompts are not reused for training or fine-tuning
- Context is supplied per request from controlled project and collection scope
- Conversation history for Secure Chat is stored inside the platform and removed when the conversation or account is deleted
- Data is not shared outside the platform as part of model training workflows
This model supports confidential AI use cases where organizations need more control than a public AI chat tool can provide.
WARNING
Even with private AI workflows, users should still follow their organization’s own rules for handling confidential, regulated, or export-controlled data.
Delivery and Deployment Model
The public product messaging describes flexible delivery options to match different security and operational requirements.
These include:
- Onsite deployment for organizations that require controlled hosting, data residency, and full infrastructure ownership
- Managed cloud services for organizations that want secure hosted operations with ongoing support, monitoring, and updates
This allows the system to fit different governance, hosting, and compliance needs.
Operational Benefits
At a system level, the platform is intended to provide several operational advantages:
- Faster response creation for RFIs and RFPs
- Better consistency across proposal and answer workflows
- Private AI use with controlled document context
- Reduced manual research through search and summarization tools
- Easier production of supporting collateral such as presentations, profiles, and images
- A single workspace for organizing documents, knowledge, instructions, and outputs
What to Explore Next
After reviewing the system overview, the most useful next pages are: