The AI Report Builder for Patents simplifies patent research by generating structured reports based on predefined or custom prompts. Users can create reports for common analyses like Commercialization Reports, Citation Impact Analyses, and White Space Analyses, or define their own objectives by selecting specific data points.
To use AI Reports, start with any type of search (semantic, Boolean, or organization-based). Select a single patent or multiple patents, then choose a suggested prompt or create a custom one. The AI processes the selected data and generates a report, which can be refined using the ‘Regenerate’ option or downloaded as a PDF.
This feature is powered by retrieval-augmented generation (RAG), ensuring that reports are based on relevant, structured patent data. Watch the video below for a step-by-step guide.
How-To Video: AI Report Builder for Patents
The AI Report Builder for Patents simplifies patent research by generating structured reports based on predefined or custom prompts. Users can create reports for common analyses like Commercialization Reports, Citation Impact Analyses, and White Space Analyses, or define their own objectives by selecting specific data points.
To use AI Reports, start with any type of search (semantic, Boolean, or organization-based). Select a single patent or multiple patents, then choose a suggested prompt or create a custom one. The AI processes the selected data and generates a report, which can be refined using the ‘Regenerate’ option or downloaded as a PDF.
This feature is powered by retrieval-augmented generation (RAG), ensuring that reports are based on relevant, structured patent data. Watch the video below for a step-by-step guide.
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We're excited to announce the release of Cypris Memory.
Q now carries context across sessions, remembering your role, research priorities, active projects, and response preferences.
Every conversation begins with a deeper understanding of your work, so Q can operate less like a blank slate and more like an agent built around you.
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What Q can now remember
- Who you are: Your role, industry, and research focus
- What you’re working on: Active projects, technologies, and topics you return to
- How you want responses delivered: Whether you prefer long, detailed answers, concise and direct responses, or more visual-heavy outputs
- What you explicitly tell it: Ask Q to remember context or preferences directly from any chat
Importantly, we designed Memory so that it should never bias the research strategy. Its impact is primarily felt at the response level, helping personalize how results are delivered while maintaining research objectivity.
You're always in control
You can manage everything Q remembers in AI Settings, located within your User Settings. From there, you can review, edit, or delete memory at any point.
Memory is isolated at the individual user level. Nothing in your memory is used to train models or leaves your Cypris instance, and you can review, edit, or delete it at any time.
Memory should make Cypris feel less like a research tool you need to configure and more like an assistant that understands your work and gets better with use over time.
As always, please feel free to reach out to our team with any questions.
Best,
Cypris Team
We’ve rolled out a major upgrade to how Cypris Q manages context across complex research workflows, cutting context usage by up to 50% across the majority of sessions.
Cypris now uses context more intelligently across images, websites, tool calls, source analysis, and Q’s internal planning. The result is more focused reasoning, less unnecessary processing, and fewer credits required to execute complex research.
Importantly, this does not reduce the number of patents, papers, or other sources Q can analyze. Instead, Q is using less context on unnecessary intermediate steps, leaving more capacity for the research itself.
More Efficient Context Across Every Session
The latest upgrade improves how Q decides what information to keep active, what to compact, and what to retrieve only when needed.
Across our internal data, these changes have reduced context usage by up to 50% for 75% of Cypris sessions. That gives Q more room for deeper analysis while improving the efficiency and cost of running sophisticated research workflows.
For users, that means longer sessions, more efficient execution, and less credit consumption on complex tasks.
Infinite Session Length
Q can now automatically compact long conversations while preserving the history of your research.
A dedicated Transcript subagent can retrieve exact details from earlier in the session when needed, allowing users to continue working across extended research workflows without losing access to prior discussion.
Deeper Source Analysis
A new Source Analysis subagent can read and reason across the full text of individual sources.
This gives Q more complete context when analyzing technical documents and allows it to go deeper into the underlying source material rather than relying only on limited excerpts.
Smarter Internal Planning
We’ve also improved how Q plans complex research tasks.
Q now builds more efficient research plans, using the tools and analysis required for the task without taking unnecessary steps. This improves reasoning quality while reducing unnecessary token and credit usage.
Optimized Web, Image, and Tool Context
Cypris now uses context more efficiently when working with:
- Websites and individual pages
- Images
- Tool calls and outputs
- Source analysis
- Q’s internal planning
By reducing unnecessary context and processing across these areas, more of each session can be devoted to meaningful analysis.
Lower Credit Consumption for Complex Research
These infrastructure improvements also translate directly into more efficient credit usage.
Complex research workflows can now require materially fewer Cypris credits to complete because Q is processing less unnecessary context while preserving the information it needs to perform the task.
Built for Longer, Deeper Research
The goal is simple: help researchers run longer, deeper, and more complex tasks in Cypris without the context limitations or unnecessary compute of general-purpose AI systems.
More improvements are already planned, including greater visibility into Q’s planning process and dedicated infrastructure for research across a wider array of documents.
Product update
Today we’re launching chemical structure drawing in Cypris Q, giving users a new way to start research from the structure itself, not just from text.
Until now, chemical prompts in Q began with written descriptions, compound names, CAS numbers, or other identifiers. Now, users can draw a compound or reaction directly in the editor, and Q will read the structure, include it in the prompt context, and analyze it through the Cypris Intelligence Layer.
This is an important step forward for chemical, IP, and R&D teams. It brings structure-first reasoning into the same environment where teams already search across patents, papers, regulatory sources, commercial data, and compound intelligence.
Draw compounds and reactions directly in Q
Users can now open the structure editor from the toolbox in Cypris Q and sketch a molecule or reaction on the canvas.
The editor supports atom and bond tools, common ring systems and functional groups, stereochemistry, R-group and S-group handling, and structure clean-up. Users can paste an existing structure or start from scratch, making it easier to move from an idea, molecule, or reaction scheme into a research workflow.
Add multiple structures to a single prompt
Q also supports multiple structures in the same prompt.
This is useful when comparing compounds, evaluating related molecules, working across a reaction, or asking Q to reason over a broader chemical set. Instead of describing each structure in text, users can provide the structures directly and ask Q to analyze them in context.
Verify structures with SMILES and InChIKey
Each drawing is converted into SMILES and InChIKey representations, both visible and copyable in Q.
This gives users a clear way to verify what Q read from the drawing and carry those identifiers into other workflows, databases, or internal systems. It also helps ensure that the structure being analyzed is the one the user intended.
Mapped through the Cypris Intelligence Layer
Once a structure is added to a prompt, Cypris runs it through the Cypris Intelligence Layer.
That means Q can connect the drawn structure to chemical synonym resolution, related compounds, regulatory sources, patents, papers, and commercial intelligence. Rather than treating the drawing as an isolated image, Q understands it as structured chemical context that can be used for deeper research and analysis.
This opens up a new class of workflow for chemical research inside Cypris. Users can now ask questions from the structure outward, using Q to reason across the global landscape surrounding a compound, molecule family, or reaction.
Available now
Chemical structure drawing is available now to all Cypris customers.
To access it, open Cypris Q, click into the toolbox in the chat window, and select Draw Structure.