Contact Rocket Vector

Causal AI products for decisions that need to move into action

Darkstar and Navigator

Prediction is not the decision. Rocket Vector builds products where evidence, causal assumptions, uncertainty, and next actions can be inspected together.

  • Darkstar turns Bayesian network work into an operational Causal AI product.
  • Navigator turns LeadScope runs into bundle-driven drug discovery evidence workspaces.
  • Bring us the decision that is stuck; we help turn it into an actionable decision workflow.
Open Darkstar
What We Fix Decision bottlenecks where prediction, evidence, and action are disconnected.
Who It Helps Model builders, drug discovery teams, technical buyers, and decision owners.
How It Ships Hosted products, preview access, private deployment, and focused implementation support.

Build and share causal models in Darkstar

Review drug discovery evidence in Navigator

Work with a procurement-ready product company

Darkstar and Navigator

Rocket Vector centers on two products: Darkstar for causal and Bayesian network work, and Navigator for bundle-driven LeadScope drug discovery evidence review.

Darkstar

Author, learn, and ship Bayesian networks.

Darkstar is the hosted Causal AI workbench for building transparent BBNs, testing evidence, interventions, and counterfactuals, learning candidate structures from data, and moving validated models into runtime delivery.

  • Author graphs, inspect posteriors, sample models, calculate lift, and share review links.
  • Run inference and layout in a protected browser WebAssembly workspace.
  • Learn discrete and continuous models with constraint-based, search-and-scoring, and optimization workflows.
  • Move models through Spark, paid workspace, SDK/runtime ports, and private deployment paths.
Open Darkstar

Navigator

Bundle-driven evidence workspaces for drug discovery runs.

Navigator turns completed LeadScope runs into authenticated workspaces with natural-language questions, exact causal tools, structured drill-downs, report views, charts, citations, and campaign handoff.

  • Open shared showcase bundles or account-owned private bundles from completed runs.
  • Review molecule, disease, lab, ranking, P/I/C, answer-bank, run-status, and promotion-gate artifacts.
  • Decide when to pursue, intervene, rescue, modify, stop, or move a candidate forward.
  • Request preview access while the release candidate is being finished.

What We Solve

The pain point is not that teams need more AI. It is that models, evidence, dashboards, rankings, and expert judgment are scattered when the next decision is due.

01

Models are trapped in technical artifacts.

Darkstar gives causal model builders a workbench for authoring, reasoning, learning, sharing, and operating BBN workflows.

02

Drug discovery signals do not agree.

Navigator helps teams compare candidates when molecular, disease, assay, target, and nanobody evidence points in different directions.

03

The next action is unclear.

Rocket Vector focuses on the decision layer: what to test, rescue, modify, stop, deploy, or share with the next stakeholder.

Darkstar

Bayesian network work belongs in shared, operational product workflows.

Darkstar is the public Rocket Vector path for BBN and causal model workflows: online workspace, Spark entry, protected browser WebAssembly, paid plans, model sharing, Learn from Data jobs, SDK ports, commercial runtime access, and private deployment conversations.

Model authoring, graph inspection, evidence entry, posterior inference, sampling, lift analysis, and model sharing.
Intervention, counterfactual, uncertainty, Model Discovery, and Learn from Data workflows for practical reasoning.
Protected runtime and commercial SDK access across Python, C++, TypeScript/JavaScript, Java, C#, R, Julia, Go, Rust, Octave, Swift, Ruby, and Lua ports.
Open Darkstar

Partner with Rocket Vector

Use Rocket Vector when the cost of the wrong next experiment, model decision, or candidate prioritization is higher than the cost of better decision infrastructure.

Bring the stuck decision

We work best when there is a real decision owner, a real workflow, and a clear reason the output needs to be used beyond a static report.

Turn evidence into a workflow

The goal is a working interface: shared model reasoning, drug discovery review, private deployment, or a focused integration your team can adopt.

Keep technical access current

Public BBN work is routed through Darkstar. Commercial API, SDK, runtime, and private-deployment paths are handled through product access or a scoped agreement.

Keep the blog visible

The Rocket Vector blog remains the place for causal reasoning examples, product thinking, drug discovery notes, and longer-form technical context.

Read the Blog

Commercial and procurement readiness

Vendor setup details stay easy to find.

  • UEIQMPBWBAHJK66
  • CAGE/NCAGE9T1B5
  • SDVOSBCertification pending

Frequently Asked Questions

Direct answers for buyers who remember the older Rocket Vector site.

What does Rocket Vector do?

Rocket Vector builds causal AI products for decision support. Darkstar serves causal and Bayesian network workflows. Navigator serves bundle-driven LeadScope drug discovery evidence review.

Is Darkstar live?

Yes. Darkstar is the public product path for Bayesian network authoring, evidence, interventions, counterfactuals, sharing, and operational model access.

Is Navigator released?

Navigator is close to release and appropriate to discuss publicly as a preview-access product. The site should invite preview requests without overstating broad public availability.

Does this replace our existing stack?

No. Darkstar and Navigator are decision layers. They help teams operationalize causal models and drug discovery evidence without requiring a rip-and-replace of every existing tool.

Is this medical advice?

No. Rocket Vector products provide computational decision support and evidence review. They are not a substitute for professional clinical, regulatory, or medical judgment.

Can we discuss a private deployment?

Yes. Private deployment, commercial runtime access, SDK paths, and focused integrations can be discussed when the workflow, users, and operational requirements are clear.

Bring Us the Decision That Is Stuck

The useful first conversation is about the decision, the evidence, the workflow, and who needs to act on the output.

Send a message

Tell us about the decision, product path, or preview conversation you want to start.

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So what do we fix?

We fix decision bottlenecks where models, evidence, and next actions are disconnected. The output should be a product workflow your team can inspect, use, and defend.