01
Connect
Read-only connectors for warehouses, databases, files and SaaS tools, with incremental sync and schema change detection.
- 50+ native connectors
- Push-down queries, no bulk copying
- Schema drift alerts
AI-native architecture
An AI platform from raw data to explained answers
Five connected layers, with AI agents at the centre, take your data from source systems to answers you can audit.
Data flows left to right. Nothing is copied out of your environment unless you choose to.
02
Model
A semantic layer that holds metrics, dimensions and joins. Deepwave drafts it from your schema; your analysts approve it.
- Metrics defined once, reused everywhere
- Git-style review and version history
- Natural-language synonyms for business terms
03
Reason
Deepwave AI agents plan multi-step analysis, test hypotheses and check their own results before they answer.
- Driver and cohort analysis
- Anomaly and trend detection
- Confidence notes on every answer
04
Deliver
Share answers as live reports, scheduled digests, embedded views or API responses.
- Slack, Teams and email delivery
- Embeddable charts
- REST and SQL endpoints
05
Govern
Access control, lineage and audit sit across every layer instead of being bolted on at the end.
- SSO and SCIM provisioning
- Row- and column-level policies
- Full lineage from chart to source column
Designed to run next to your data
Queries are pushed down to your own warehouse wherever possible. Deepwave stores metadata and results, not copies of your tables.
ExperienceWeb workspace, chat, embedded views, API
AI reasoningPlanner, query engine, verification
Semantic layerMetrics, dimensions, policies
ConnectorsWarehouses, databases, files, SaaS
Answers you can audit
Each result carries the query, the data sources, the metric definitions and the time it ran. Reviewers can reproduce any number in one click.
- Query and lineage on every result
- Human-readable change log for metrics
- Exportable audit trail