Private-first AI data workspace Data stays privateAnalysis shows its work

DataForest / Product

Keep every analytical step local

From local machine learning to reviewable reports, DataForest keeps professional analysis clear and traceable.

ANALYSIS / LIVE APP SCREEN
DataForest / Professional analysis
Professional analysis, clearly presentedANALYZE
Review the complete analysis plan and process at any time.
Rich visualizations appear directly in messages, with clear conclusions.
17 chart families
Professional analysis Local prediction and classification
PPTDOCXPDFXLSX

01 / ANALYZE DEEPLY

Professional analysis, clearly presented

Run local prediction and classification models; plans, records, charts, and conclusions remain in the same task.

  • Local prediction and classification Run professional machine-learning algorithms directly on your own machine.
  • Plans and records Review the complete analysis plan and process at any time.
  • 17 chart families Rich visualizations appear directly in messages, with clear conclusions.
  • Fast reporting Embedded templates export PPT, Word, PDF, and Excel; code can create a fully custom report.
Pricing
SECURITY / LOCAL BOUNDARY
DataForest / Local protection
project / customer-churn input / raw-data sandbox / task-024 output / reports
Storage guardrail Execution guardrail Output guardrail

02 / KEEP LOCALLY

Three technical safety guardrails

Three technical safety guardrails constrain storage, execution, and output so sensitive data never leaves your workspace.

  • Storage guardrail Project input sources and output directories are clearly isolated.
  • Execution guardrail Each task and code run executes in an isolated sandbox.
  • Output guardrail Each project has independent output storage, with strict limits on cross-project reads and uncontrolled output.
  • Path de-identification The model never receives the real local directory path.
Pricing
WORKFLOW / EVIDENCE TRAIL
DataForest / Focused execution
1Plan before executionComplex work begins with an analysis path anchored to the task.
2Evidence follows conclusionsEvery key conclusion is supported by the evidence behind it.
310,000+ file workflowsLarge file-processing work runs steadily and smoothly.
Evidence follows conclusions

10,000+ file workflows
Evidence follows conclusions

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03 / STAY FOCUSED

Plan first; conclusions stay on task

Plan first, evidence follows conclusions, and conclusions stay anchored to the task so complex, long-running work stays focused on the current goal.

  • Plan before execution Complex work begins with an analysis path anchored to the task.
  • Evidence follows conclusions Every key conclusion is supported by the evidence behind it.
  • 10,000+ file workflows Large file-processing work runs steadily and smoothly.
  • Clearer conclusions with the same token budget Compared with a general conversational agent, the same token budget reduces hallucinations by 80% and yields more accurate, clearer conclusions.
Pricing

Pricing built for simple adoption

Start with a free 1-day trial, choose monthly flexibility, or pick the recommended annual plan for ongoing use.

View full pricing
Common questions

Common questions

Answer core questions about downloading the app, local control, language support, and self-serve subscription choices.

Is my data stored locally or in the cloud?

DataForest is designed local-first. Your data stays on your infrastructure unless you explicitly choose another operating model.

What file formats are supported?

The product direction covers common analytics formats such as CSV, JSON, Parquet, spreadsheets, and SQL-connected sources.

Do you offer team onboarding?

Yes. Team plans can include setup guidance for local deployment, shared workspaces, and rollout inside your own operating environment.

Can DataForest fit into existing workflows?

That is the goal. We position the workspace around your current review, analysis, and reporting flow rather than forcing a generic process.

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Contact

Suggested email structure: include your question, the full email address of the account you use to sign in, and any relevant context so we can follow up efficiently.