Methodology
How a prior-art search becomes reviewable.
Serious patent work needs more than a fluent answer. A useful AI-assisted search should show its objective, boundaries, evidence, limitations, price context, and review state in one inspectable report.
Platform output
What the platform prepares for review.
A useful search should leave the reviewer with a trail they can inspect: the review question, source limits, exclusions, candidate references, citation anchors, open limits, and next searches.
The public sample report and sample search flow show that structure with sample material only. They are a way to evaluate the review trail before sending confidential facts or starting paid work.
See the prior-art search path- Review question
- The exact prior-art question the report is organized to test.
- Source limits
- The public sample sources, exclusions, and practical limits around the review.
- Candidate references
- References a reviewer can inspect, challenge, or carry into a deeper search.
- Citation anchors
- Passages and locator fields tied to the candidate, not unsupported model conclusions.
- Open limits
- What remains uncertain and which follow-up searches would reduce that uncertainty.
- Reviewer handoff
- A clear boundary between source evidence, system organization, and professional judgment.
Before live work
What to check before you start a search
Start with the sample report. It shows the question, cited references, weak spots, and review limits so your team can decide whether to create an account, request setup, or price live work.
Review setup options- Fit
- Does the sample match the kind of patent review your team needs to supervise?
- Evidence
- Are cited references, source anchors, weak spots, and limits visible enough to challenge?
- Control
- Are online terms and price approval clear before live search work starts?
- Next step
- Can your team move from the sample to an online plan, enterprise setup, or a priced search without a sales call?
Search anatomy
From practitioner question to review report
The system keeps language models in the parts of the job where they help most: planning, synthesis, and explanation around retrieved evidence. Search scope, approval, and source limits stay explicit.
Scope the request
Practitioner instructions are normalized into a search objective, target facts, exclusions, jurisdictions, outputs, and review expectations.
Price before search
Paid work is priced before retrieval starts, so the search type, expected output, and approval step are clear before work moves.
Search bounded branches
Bounded search paths keep scope and quoted usage clear before broad corpus work begins.
Assemble evidence
Candidate references are paired with source passages, family context, coverage notes, and review status instead of unsupported summaries.
Review consistently
Results are compared after the search is narrowed, while dates, family data, and jurisdictions stay explicit.
Preserve review records
The report carries limitations, search history, price context, candidate records, and version history so reviewers can inspect the path taken.
Evidence before answers
What a reviewer should be able to inspect
The useful question is not whether an AI system can sound confident. It is whether a partner, associate, client, or security reviewer can see what happened and decide what still needs human judgment.
- Search objective
- The precise question the search was meant to support.
- Target source
- The patent, publication, product page, or non-confidential disclosure used to frame the search.
- Candidate families
- Grouped references with family and self-art risk called out.
- Evidence passages
- Source snippets tied to the candidate, not free-floating assertions.
- Coverage limitations
- What was searched, what was skipped, and what needs attorney follow-up.
- Search history and price trail
- Price, search, regeneration, and export context kept with the work product.
Guardrails
Built for supervision, not blind reliance
ipstrategy.tech is designed for attorney-reviewable patent work: bounded inputs, visible price controls, source-backed reports, and explicit limitations where a search should not be overread.
- No confidential client facts in the public sample.
- Live searches require account setup, online terms, and price approval before they run.
- Reports are support artifacts for attorney review, not legal opinions.
- Unsupported claims, complete-search guarantees, and black-box citation output are deliberately avoided.
Use the sample to judge the review path.
A controlled pilot should test whether the report helps real reviewers move faster with better supervision: useful references, clear limitations, predictable pricing, and less mystery in the path from request to report.