Many active investors still rebuild their view of a name by hand after every earnings call. The chart lives in one place, narrative notes live in a document, and the quant view of upside, downside, and odds sits in a spreadsheet or a risk system. Every time the story changes, they have to eyeball channels, re‑read transcripts, adjust a target price, and then explain that change to a PM or an IC with no single surface that ties it all together.
VecViz closes that gap. Instead of treating “technical”, “fundamental”, and “quant” as separate worlds, it links them around one question: where should this ticker trade, given its price structure and the narrative that drove it over time.
VecViz is built for fundamental analysts who want their view of a ticker on the same footing as quant and technical analysis, for PMs and traders who want narratives and probabilities anchored to the chart, and for quants who need an explainable model they can show to non‑quants.
Inside the OpenBB Workspace, that view sits next to whatever else matters to the team and is fully in reach of the OpenBB Copilot, so agents can work across chart, narrative, and probability distributions without leaving the same environment.
Inside the VecViz model
VecViz starts from the price chart but does not stop at drawing a couple of trend lines. The Vector Model systematically identifies and scores price channels, links LLM‑sourced and characterised narrative elements (“VecEvents”) to those channels, and pushes both into machine‑learned price probability distributions. The result is a structure where every target price, risk band, and analogue ties back to both the tape and the underlying story.
VNA Target Price
At the centre is the VNA Target Price, VecViz’s Vector Narrative Alignment methodology. It finds where a ticker’s price should sit relative to the centre of its channel trajectories, based on an LLM‑sourced narrative timeline, cross‑ticker adjustments for excess bullish or bearish bias versus the market, and the Vector Model’s 6‑ to 12‑month base‑case probability distributions.
Inside OpenBB, VecViz MCP tools let you pull VNA Target Price odds by forward date from the Price Probability widget and adjust that target directly when your view of the narrative changes, instead of overriding it in a spreadsheet.
V‑Score Spider Chart
To make this explainable, VecViz ships the V‑Score Spider Chart, a machine‑learning‑based ranking of expected forward price return with its drivers visible. Each axis shows the percentile rank of a key channel or probability feature, and the chart overlays the closest historical analogues from the highest and lowest return quintiles. The result is one view that places your current ticker alongside its bull analogue and its bear analogue, spanning six horizons from one day to one year forward.
Price Probability Forecast
Around that core, VecViz adds a few focused panels that make the model usable day to day. A Price Probability Forecast view shows Vector Model price percentiles to the downside and upside across six forward horizons, explicitly reflecting jumpy and asymmetric volatility, with a sigma‑model overlay so you can see where a simple normal approximation diverges.
Vector & Sigma VaROaR History
A VaR and OaR history view gives historical 95 and 99 percentile Value at Risk and Opportunity at Risk for both the Vector Model and a sigma‑based view, which helps you see whether a target or scenario sits inside or outside what the model treats as a typical tail for that name.
For options work, VecViz exposes Vector‑derived option fair value estimates across a wide range of strikes and expiries, so you can compare model‑implied distributions for two tickers without rebuilding the math yourself.
VV Data Table
Finally, the VV Data Table provides about thirteen months of daily history for key VecViz metrics as a structured table you can sort, filter, and combine. You can filter it manually or call the VecViz MCP screener, and because it lives inside OpenBB, it is easy to merge with other data sources via Copilot, whether that is simple valuation ratios, factor scores, or anything else already in your Workspace.
VecViz’s app on OpenBB: analytical widgets and MCP tools
VecViz ships as an OpenBB App with six analytic tools exposed as widgets and a growing set of MCP tools that turn those analytics into building blocks for agents.
In a typical Workspace, an analyst will pin the VNA Target Price panel, V‑Score Spider Chart, Price Probability Forecast, VaR/OaR history, option fair values, and the VV Data Table alongside their own holdings, benchmark, and risk views. Because these widgets live inside the OpenBB Workspace, the OpenBB Copilot and custom agents can pull VecViz data, cross‑reference it with other apps, and write back updated narratives or targets without leaving the dashboard.
Under the hood, the VecViz app also exposes MCP tools such as the VV screener, the VecViz Report, and the VecEvents tool that lets agents read transcripts against the existing narrative timeline. And because the MCP servers are available inside Workspace, teams can add their own skills on top of the same model rather than starting from scratch.
App subscribers also receive starter prompts from VecViz that show how to chain those tools together into longer workflows.
One OXY workflow, end to end
Most PMs update a target price after earnings by juggling a chart, a few ratios, and a transcript in different tools. Inside OpenBB, VecViz turns that manual process into a repeatable agent workflow.
In the example below, VecViz founder Rodger Coyne starts with the VV Data Table screener to find tickers where the VNA Target Price, V‑Score, and upside/downside returns all line up, then calls the VecViz Report MCP tool on a shortlist that includes Goodyear, Freeport, and Occidental. The report shows where each ticker’s key metrics sit on a z‑score basis versus their own history and versus the cross‑section, so Goodyear and Freeport drop out quickly while OXY surfaces with stronger, broadly positive scores.
From there, he pulls OXY’s most recent earnings transcript into context alongside the existing VecEvents and runs a VecViz skill that asks the OpenBB Copilot to re‑read the transcript, confirm or adjust those events, and propose any new ones the model missed. The same workflow works just as well on other text‑based content, whether that is internal analyst notes or external research, as long as you bring it into the Workspace context.
In this case, the agent confirms some events, changes others, and flags a new Middle East operational disruption; VecViz then pushes those changes back through its Vector Model to knock roughly eleven dollars off the original VNA Target Price path, with the reasoning traceable back to specific passages in the transcript.
All of this happens on a single OXY dashboard that also shows VecViz channels, the V‑Score spider, price probability distributions, and VaR/OaR history next to positions and risk. Each quarter, the PM only needs to bring in the new transcript and trigger the skill, and the agent does the rest in a way that can be inspected, explained, and evolved as their process matures.
How to get started
To use VecViz inside OpenBB, connect the app from the OpenBB App Marketplace and add a VecViz API key.
The current VecViz subscription costs $19 per month, billed monthly with no long‑term lock‑in, and it covers all six analytic tools, the associated MCP tools, and around 140 popular US equity and ETF tickers, with more coming online over time.
You can sign up here.
If you are already running your equity process in OpenBB, VecViz gives you one place where chart structure, narrative, and probabilistic targets live together and where both analysts and agents can work against the same model.
