A Software Invention Disclosure Checklist for Engineering Teams

A good software invention disclosure explains the problem the software solves, how the system is built, how data moves through it step by step, what is new compared with existing approaches, what alternatives would also work, and what measurable improvement it delivers. Engineers already know most of this. The checklist below organizes it in the form a patent attorney or agent needs to draft a strong application.

This is a worksheet for after you have engaged a patent practitioner (a registered patent attorney or agent). Keep it inside your company until conflicts are cleared and the engagement is in place, then share it through the channel your practitioner provides.

When to use this checklist

Use it once you have decided to pursue an application and your practitioner has asked for technical material. Most of the answers already exist in design documents, architecture diagrams, tickets, and code reviews. The work is mostly gathering and organizing, not writing from scratch.

A disclosure does not need polished prose or legal language. Bullet points, diagrams, whiteboard photos, and pseudocode are all useful. Accuracy and completeness matter far more than presentation, and the inventor interview fills the gaps.

1. The problem and how it was handled before

Start with the problem, described in technical terms. What was slow, unreliable, expensive, insecure, or impossible before? Who or what experienced the problem: users, servers, devices, networks?

Then describe how the problem was handled before your solution, both by your own earlier versions and by other products or published approaches you know about. Note what was wrong with each. This context helps the practitioner identify what is actually new and frame the application around it.

2. System overview

Describe the system at a level a new engineer on the team would need on their first day:

• The main components and what each one does
• Where each component runs (client device, server, cloud service, embedded hardware, edge device)
• How the components communicate
• External systems, services, or data sources the system depends on

An architecture diagram is often the single most useful item in a software disclosure. Rough is fine. Patent figures are prepared later from it. Architecture alone is not always enough, though: where the claims may describe what a component does in functional terms, the practitioner may also need the specific steps, rules, or calculations that carry out each function, so the claims are supported and not limited to a result.

3. Data flow and processing steps

This is the core of most software disclosures. For the key operation, describe the sequence of steps from input to output:

• What data comes in, in what form, and from where
• Each processing step, in order, and what it does to the data
• Decision points and the conditions that select each branch
• What is stored, sent, or displayed at the end

Be specific about how each step is performed, not only what it achieves. “The system optimizes the route” describes a result. “The system builds a weighted graph from the last 30 days of delivery times and recomputes edge weights every 15 minutes” describes how. Patent law requires the application to describe the invention and enable a skilled person to make and use it (35 U.S.C. 112(a)). There is a second reason as well. Depending on how a claim is worded, a claim element defined by its function, without reciting sufficient structure, may be treated as a means-plus-function limitation under 35 U.S.C. 112(f). If that happens, the claim is limited to the corresponding structure described in the specification, which for software is generally an algorithm, and missing algorithmic detail can create problems (MPEP 2181). Pseudocode, flowcharts, and sequence diagrams help here.

4. What is new and what is known

Separate the parts of the system your team created from the parts that are standard. Most software products use well-known frameworks, libraries, protocols, and algorithms. Listing them is useful because it tells the practitioner which parts need little description and which parts need a lot.

Then identify, as precisely as you can, the specific ideas that differ from earlier approaches. A helpful test: if a competitor wanted to copy the advantage your system provides, which part would they need to replicate? That part is usually where the claims should focus.

If you used open-source components or code from a collaborator in the inventive portion, note it. It can raise ownership and licensing questions your practitioner will want to know about.

5. Alternatives and variations

List other ways the invention could be implemented, including ones you considered and rejected:

• Different algorithms, models, or data structures that could perform the same step
• Different hardware or deployment options (on-device, in the cloud, split between them)
• Ranges for key parameters, such as thresholds, window sizes, or update intervals, rather than only the values you chose
• Simpler or more advanced versions you might build later

Alternatives are easy to overlook because engineers naturally describe the version they shipped. An application that describes only one implementation can leave room for a competitor to design around the claims with a minor change. Variations also support continuation applications later, since claims must find support in the specification as filed.

6. Measured results

Describe the technical improvement in measurable terms where you can: reduced latency, lower memory or bandwidth use, higher accuracy, fewer errors, better battery life, improved security. Benchmarks, before-and-after comparisons, and test results are all useful.

Results serve two purposes. They help the practitioner explain why the invention matters, and for software, describing a concrete improvement in how a computer or system operates can be relevant to patent eligibility under 35 U.S.C. 101. USPTO guidance on eligibility changes periodically, so your practitioner will apply the current version.

7. Additional items for AI and machine learning

For AI and machine learning inventions, add:

• The model type and architecture, and why it was chosen
• The training data: what kind, where it comes from, and how it is prepared or labeled
• The training process, including any unusual loss functions, training stages, or feedback loops
• How the trained model is used at inference time, and what happens with its output
• Which of these is new: the model, the training method, the data preparation, or the way the output is applied

The last point matters most. Many AI inventions are not new models. They are new ways of preparing data, combining models, or applying model outputs to a specific technical problem, and the application should be built around whichever one is actually new.

8. People and dates

Record who contributed to the ideas (not just who wrote the code), including contractors and people who have since left. Inventorship is determined later from the claims, so a complete list of contributors helps your practitioner make that determination correctly.

Also list relevant dates: when the idea was first developed, first internal demo, any public release, beta, demo, publication, or presentation, and any planned launches. Version control history and design documents often establish these dates.

The checklist

Copy this list into an internal document and fill it in:

• Problem: what was wrong before, and for whom
• Prior approaches: your earlier versions and others you know of, with their limitations
• System overview: components, where each runs, and how they connect (with a diagram)
• Data flow: inputs, each processing step in order, decision points, outputs
• What is new: the specific ideas that differ from earlier approaches
• What is standard: frameworks, libraries, and known techniques used
• Alternatives: other algorithms, deployments, parameter ranges, and future versions
• Results: measured improvements and how they were measured
• AI/ML details, if applicable: model, training data, training process, inference, and which is new
• Contributors: everyone who contributed to the ideas, including former team members and contractors
• Dates: first development, demos, releases, publications, and planned launches

A practical takeaway

The most common gap in software disclosures is the step-by-step detail of how the key operation works, followed closely by missing alternatives. If your team gets those two right, the inventor interview can focus on refining the claims instead of reconstructing the system, and the finished application will be both stronger and faster to prepare.