Nova OS

Key Highlights
- Nova OS is an AI research application that helps users turn complex questions into source-linked reports, evidence reviews, hypothesis suggestions, and early research plans.
- Adaptive research agents: The engine divides questions into specialist investigations, searches scholarly sources, checks selected claims, and investigates evidence gaps within configurable limits.
- Inspectable evidence: Users can review supporting passages, source links, study comparisons, and limitations. Integrity checks can reject unsupported material or return a clearly labeled limited-evidence digest.
- Private research notebooks: Account-scoped notebooks support PDF, text, and Markdown uploads, passage search, source-based AI questions, saved notes, and handoff into full research.
- Useful research exports: Supported formats include PDF, Word, Markdown, study-comparison CSV, BibTeX, RIS, and downloadable review bundles.
- Developed application foundation: Password and Google sign-in, saved research history, progress tracking, follow-up research, usage controls, backup utilities, automated tests, and CI are implemented.
- Commercial development opportunity: A new owner can build on the existing product by introducing paid plans, targeting a specific research audience, improving hosting, and validating research quality with independent specialists.
Operations
Nova OS is a browser-based research workspace built around a Python research engine, a JavaScript frontend, and SQLite storage. Users enter a question, optionally review an editable investigation plan and source preferences, then start a research job. The application displays progress and retains reports and supporting artifacts for later review.
The notebook workflow complements literature research. Users can upload their own documents, search extracted passages, ask source-based questions, save notes, and select material for a broader investigation. Notebook retrieval currently uses keyword search rather than vector-based semantic search.
The repository does not currently contain an integrated subscription checkout or payment-processing system. Subscriptions, research credits, team access, and customized deployments are potential business models for a new owner, rather than established revenue streams.
Routine operations include monitoring research failures and provider usage, maintaining backups, updating dependencies, supporting users, and maintaining the domain and authentication configuration. The documented deployment uses a Windows laptop behind Cloudflare Tunnel, so availability depends on that machine and its internet connection. Dedicated hosting would be an important next step for broader commercial operation.
Estimated owner commitment: A provisional planning allowance is 5–10 hours per week for maintenance and support at a small beta scale, excluding development, marketing, and hosting migration. This is an estimate, not a measured historical workload.
Customers
Nova OS is designed for postgraduate researchers, independent researchers, technical founders, and early-stage R&D teams. Materials science, chemistry, and biochemistry are particularly relevant audiences for its evidence-review and hypothesis-planning workflows.
Typical uses include investigating a literature question, comparing published studies, identifying missing evidence, organizing uploaded papers, and preparing an initial research plan for expert review.
The English-language web interface can serve an international audience, subject to hosting and provider availability. However, verified customer geography, active-user counts, retention, repeat usage, and paying-customer figures are not available in the materials reviewed.
The product includes a public quick-answer demo and an account-based research workspace to support visitor onboarding. Acquisition channels a new owner could develop include educational walkthroughs, research communities, university outreach, and partnerships with specialist consultants. These are growth opportunities, not proven acquisition channels.
Financials
The workspace does not contain verified revenue statements, payment-processor reports, a profit-and-loss statement, or customer billing records. No claim of recurring revenue, profitability, financial growth, or established paid subscriptions is made in this description.
The acquisition should therefore be evaluated primarily on its software assets, implemented workflows, documentation, and development potential unless separate financial records are supplied.
Operating expenses depend on hosting, domain renewal, AI-model usage, search-provider requirements, storage, and maintenance. Application-level quotas help limit usage but do not guarantee a fixed monthly cost or unlimited free operation.
No financial seasonality or revenue trend can be substantiated from the repository. Any seller-provided earnings, expenses, or traffic figures should be supported separately during due diligence.