Standard Metrics is upgrading our AI Analyst with charting functionality and web search.

At the beginning of this year, we launched our AI Analyst, an in-app agent that accesses and analyzes portfolio data stored by firms in the Standard Metrics platform to streamline portfolio reviews, analyze across multiple data sources, and simplify ad-hoc analysis and external LP reporting. Since launch, our users have had thousands of conversations with our AI Analyst, and we’ve gained valuable insights about what new capabilities to add next.

Our latest launch speaks to two of the top requests by those customers: in-app charting and web search. In-app charting allows investors to move from a natural language query to a beautiful visual in seconds. Web search combines the knowledge of the internet with the data of a portfolio to help VCs better understand fund performance within a global context.

We dive into the new releases and what else has changed about the AI Analyst since launch below.

Web search in AI Analyst: The context you need beyond your portfolio

With the launch of web search, the AI Analyst now helps investors enrich portfolio context within the broader private markets information ecosystem. Want to compare your portfolio company’s performance to a publicly traded one? Want to track portfolio sentiment online? Curious about how a recent news headline might affect your portfolio? Need to search across the internet for financing rounds across your portfolio that have been in the news but that you may not have been privy to? Web search unlocks all these workflows and more.

The AI Analyst can now search the web as well as read specific URLs and extract content from them. This unlocks:

• Basic web searches: “What are the top stories in crypto today?”
• Searches anchored to a specific portfolio company or companies: “Summarize recent news about XYZ company in my portfolio.”
• Internal data vs. public data comparisons: “Compare our portfolio company XYZ to Salesforce by pulling Salesforce’s latest publicly reported metrics from the web.”
• Read pages and extract a specific fact: “I’m writing an LP update and want to look at a top company in a similar industry for comparison. From this article, how much did Sam Altman’s brain-computer interface startup Merge Labs raise and who led it? https://techcrunch.com/2026/01/15/openai-invests-in-sam-altmans-brain-computer-interface-startup-merge-labs/”
• Read multiple pages and compare: “Compare portfolio company XYZ to Snowflake and Databricks on pricing by reviewing these two links https://www.snowflake.com/en/pricing-options/ and https://www.databricks.com/product/pricing”

Below, the AI Analyst looks into whether a firm should make a follow-on investment into their portfolio company by comparing company performance to public comps.

Charts in AI Analyst: From query to visual in seconds

Charting functionality in the AI Analyst will help our customers answer ad-hoc questions, quickly visualize data, and share insights with an LP or another member of the team.

Newly unlocked charting features in our AI Analyst include:

• Numerous chart types to highlight trends over time, mix questions, relationships between two variables and more: Line charts, area charts, pie charts, and scatter plots, as well as horizontal, vertical, stacked and grouped bar charts are all now supported in the AI Analyst
• Easy explanations, titles, legends and more next to chart visuals: Get the TL;DR alongside the chart, all with one simple prompt
• Charts, without the work: No SQL queries, no dashboards. Just charts in-app, in-seconds via simple prompts like “Show me quarterly burn for XYZ Company over the past year” or “How is our capital allocated across funds?”

Below, our AI Analyst charts total unrealized gains for a firm across its portfolio.

What else has changed since we launched and what’s next

We’ve shipped many other improvements to our AI Analyst since our initial release in January, including:

• Structured investment data and investment metrics by fund in AI Analyst: Answer aggregated questions like “Who are we co-investing with most frequently?” or “What’s our total invested capital by fund?” across an entire portfolio.
• More intuitive sector understanding and filtering: When prompted about sector, the AI Analyst now defaults to the sectors that a firm uses to classify its own portfolio companies.
• Constant UI and UX updates: From dynamically generated chat titles to the ability to delete old chats, there are near weekly updates to improve the quality of the product experience for our customers.

Over time, we plan to add benchmarking, IR, and unstructured data to the AI Analyst, as well as further UX improvements. If you’re a current customer, we’d love to learn more about how you’re using web search or charts and any other features you’d like to see next. If you’re a prospect and would like to learn more, reach out via the form below.