Tellius is an AI business intelligence platform for finance, revenue and pharma commercial teams, with AI agents that run recurring analysis. Sold by quote.
Tellius explains why a business metric moved and hands the answer back as finished work, from a chart with a written narrative to a slide deck. It connects to the data a company already keeps in its cloud warehouse and puts an AI analyst called Kaiya on top of it. Kaiya watches the numbers that matter, investigates when one changes and checks every figure against the source rows. Tellius, Inc. of Reston, Virginia, founded in 2016, builds the platform and sells nothing else. The platform is organised into named parts. Connect reaches Snowflake, Databricks, Redshift and BigQuery and pushes each query down to the warehouse, so no extract or second copy is made. Kaiya Architect builds the semantic layer through conversation, defining joins and calculated metrics that every chart then shares. Conversational AI answers typed questions from that governed model, while AI Insights runs root cause, key driver, cohort and anomaly analysis without being asked. Vizpads cover drag-and-drop dashboards with generated narratives, and AI Agents plan a mission, rerun it on fresh data and email the finished deck. Tellius is built for finance, revenue and commercial teams in large companies, with industry versions for pharma and life sciences, consumer goods, healthcare, software and financial services. It fits best where the data already sits in a cloud warehouse and analysts face a backlog of recurring questions. It runs hosted on Tellius Cloud, and it can also be deployed in a customer's own cloud or on-premises. Buyers agree terms with the sales team, which quotes each deployment. A typical job is the month-end variance review, where the AI worker compares actuals with plan, names each driver and drafts the slides. Pharma field force and market access teams use it to follow field effectiveness and payer contracts with data drawn from Veeva and IQVIA. Kaiya Everywhere carries the same governed answer into Slack, Teams and the browser, so a question asked in a chat thread returns the number the dashboard shows. For a finance or commercial team that rebuilds the same review every cycle, Tellius turns that analysis into a briefing delivered on time.
Features
- Included: Drag-and-drop report builder
- Included: Live connection to cloud data warehouses
- Included: Scheduled data extract refresh
- Included: Semantic data model with governed metrics
- Included: Self-service data preparation
- Included: Natural language questions on data
- Included: Ad hoc drill-down and cross-filtering
- Not included: Paginated print-ready reports
- Included: Scheduled report subscriptions by email
- Included: Automated anomaly and trend insights
- Included: Row-level security by user attributes
- Not included: Data lineage and impact analysis
- Not included: Version control and deployment pipelines
- Not included: Native mobile apps for reports
- Not included: On-premises data gateway
- Not included: Free viewer seats for report consumers
- Included: Self-hosted BI server option
Additional Features
- Conversational AI questions answered from governed data
- Kaiya Architect semantic layer built through conversation
- Kaiya Everywhere answers in Slack, Teams, the browser and MCP
- Kaiya Apps that reason over company data
- AI Insights root cause and key driver analysis
- Automated anomaly and cohort detection
- Proactive Intelligence Feeds
- Vizpads drag-and-drop dashboards
Best for
- Commercial pharma and life sciences teams in brand, field force and market access
- Finance and FP&A teams running a month-end variance review every cycle
- Revenue and RevOps teams that need the reason a metric moved
- Consumer goods and eCommerce companies analyzing price, volume and mix
- Procurement teams tracking spend against plan
- Enterprises with data in Snowflake, Databricks, Redshift or BigQuery
- Organizations that must run analytics in their own cloud or data center
Use cases
- Explaining a month-end variance against plan
- Automating recurring executive and board reporting
- Measuring field force effectiveness in pharma sales
- Analyzing payer contracts for market access
- Asking questions of warehouse data in plain language
- Finding the key drivers behind a metric change
- Catching anomalies in commercial KPIs without manual checks
- Building a governed semantic layer from raw warehouse tables
- Emailing a finished briefing deck before a recurring meeting
- Embedding white-labeled analytics in another application
- Preparing and joining source data without code
- Training and scoring machine learning models on business data
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