An analytics OS that knows what to do with the data.
Data intelligence vault, market & competitor research, forecasting simulator, AI copilot, and a final intelligence report — five modules, one project at a time, every answer cited to the chunk it came from.
One project. Five disciplines. One command center.
Each analytics project is its own workspace with isolated persistence and memory. Open a module; it remembers everything you've done in the others.
- 01
Data Intelligence Vault
Upload every dataset in the matter. We profile, chunk, and tag with dates, companies, metrics, KPIs, categories, trends, anomalies and events. Ask in natural language — answers come back with the exact citation.
- Citeable analytics blocks
- Entity index across 8 kinds
- Anomaly + trend intelligence
- Insight suggestions + scoring
- Numeric intelligence score
- 02
Research & Market Intelligence
A market index that understands your project. Natural-language search, trend tracking, competitor snapshots, industry benchmarks and forecasts.
- Realtime market signals
- Competitor intelligence
- Industry benchmarking
- Forecasting models
- Recommendation generation
- 03
Analytics Simulation Engine
Project forward, stress-test what-ifs, and quantify the swing from each decision. Scenarios are saved per project and diffable side-by-side.
- Forecasting simulations
- Growth projection modeling
- Revenue simulation
- Market movement analysis
- Predictive decision analysis
- 04
AI Analytics Copilot
A drafting workspace that turns the data and forecasts into reports, dashboards and decisions — every claim grounded in a cited chunk.
- AI-generated insights
- Multilingual analytics assistance
- Voice-to-insight drafting
- Automated reporting + dashboard summaries
- Workflow + task prioritization
- 05
Final Intelligence Report
The one-page truth — health, risk, forecast confidence, growth opportunity, and the three actions today that most move the numbers.
- Business health · risk · forecast confidence
- Growth opportunity analysis
- KPI strength / weakness map
- Anomaly + missing-data summaries
- Strategic next actions
The same four steps, every project.
- 01
Create the project
Title, organization, domain, objective. The project is a workspace with its own memory.
- 02
Load the data
Every Excel, CSV, JSON or PDF is profiled and chunked into citeable analytics blocks. Entities are indexed across the project.
- 03
Ask · research · simulate
Chat with the data. Search the market. Run the forecast. Each module sees the project's full state.
- 04
Walk in ready
Final report: business health, risk, forecast confidence, growth opportunity, and the three actions today that most move the numbers.
A tool you can put in front of the board.
Confidentiality
Every project is isolated; per-project memory, per-project access. Datasets are encrypted at rest and in flight.
Cite-back, always
Every claim is anchored to the dataset, chunk and date it came from. Nothing the copilot says is unsupported.
Auditable trail
Every interaction is logged with the version of the data and the prompt. You can reconstruct any conclusion.
No training
Your data is never used to train a foundation model. Enterprise tenancy with data-residency controls.
Walk into the next review carrying the whole record.
A workspace for analytics teams that want every citation, every entity and every insight on the same page.