Data product design
Curated, contracted datasets and APIs treated like products — with owners, SLAs and roadmaps.
Platforms & Products
Enterprise Data Products
Package data into governed products with contracts, quality SLAs, and AI-ready interfaces.
- 10×more users than dashboard-only delivery
- <1squery response on curated products
- 100%of data products contracted and versioned
Capabilities
Data people can actually use
Turn enterprise data into trusted, usable products for AI and analytics consumers.
Conversational analytics
Natural-language interfaces that let anyone query governed data safely.
Embedded intelligence
Insights delivered inside the tools where decisions happen — not another dashboard.
Monetization-ready platforms
Customer-facing data products with metering, entitlements and billing hooks.
How it works
From data exhaust to decision products
Warehouses full of tables create no value until someone can act on them. We productize your data — governed underneath, effortless on top.
Product thinking
Datasets with owners, contracts and SLAs
Each data product gets a schema contract, quality guarantees, an owner and documentation — so consumers can build on it without asking permission or fearing silent breakage.
- Versioned schema contracts with breaking-change alerts
- Quality SLAs monitored and published
- Self-serve catalog with lineage and documentation
Ingest→
Chunk→
Embed→
Index→
Retrieve
PDFConfluenceSharePointSQLTicketsEmail
Grounded answer…with citations [1] [2] and permissions applied
Natural language
Ask the data anything — within the guardrails
Conversational interfaces over your governed semantic layer: business users ask in plain language, the system generates validated queries against approved definitions, and every answer shows its work.
- Text-to-SQL constrained to governed semantics
- Answers with the underlying query and sources shown
- Row-level security respected in every response
Copilot
Draft renewal summary for Acme Corp
3 accounts show churn risk — view analysis
Ask anything…
Embedded delivery
Insights where decisions are made
Churn scores in the CRM, stock alerts in the buyer's workflow, margin flags in the quoting tool — we deliver intelligence into operational systems, where it changes behavior.
- Insights pushed into CRM, ERP and ops tools
- Alerting on thresholds, anomalies and trends
- Customer-facing analytics embedded in your product
99.9%Uptime
1.2sp95 latency
$0.021Cost / task
QualityCostLatencyDrift
Use cases
Where data products delivers value
Self-serve analytics
Business teams answering their own questions against governed data.
Customer-facing analytics
Data features and dashboards embedded in your product, ready to bill for.
Operational intelligence
Scores and alerts delivered into frontline tools in real time.
Executive reporting
Automated narrative reporting grounded in governed metrics.
Data monetization
External data products with entitlements, metering and APIs.
ML feature foundations
Contracted features feeding models with documented lineage.
Delivery
How we build it
We start from the business outcome, then design agents, models, tools and guardrails that can survive production — not just a demo.
- Production-ready architecture
- Secure tool integrations
- Measurable business KPIs
- Operate & improve playbooks
-
1
Discover
Map workflows, data, constraints and ROI.
-
2
Architect
Define models, tools, memory and trust boundaries.
-
3
Build
Ship a production-ready system with evals and observability.
-
4
Scale
Optimize cost, quality and adoption across teams.
Adoption was our failure metric for years — beautiful dashboards nobody opened. The conversational layer changed everything: weekly active users of data went up tenfold.
Works with your stack
Built on the tools you already run
We integrate with your models, clouds, data platforms and enterprise systems — no rip-and-replace.
- Snowflake
- Databricks
- BigQuery
- dbt
- Cube
- Looker
- Power BI
- Anthropic Claude
- OpenAI
- Postgres
- Kafka
- Fivetran
FAQ
Common questions
Text-to-SQL sounds risky. How do you make it safe?
By constraining it: generation targets a governed semantic layer with approved metrics and joins, queries are validated before execution, results respect row-level security, and every answer shows the query it ran. Accuracy is eval-tested on your real questions.
How is a data product different from a dataset?
Ownership, contract and consumers. A data product has a defined schema, quality SLAs, documentation and a team accountable for it — so others can depend on it the way they depend on an API.
Can we monetize our data with this?
If you have data your customers or partners value, yes — we build the entitlement, metering and API layers that turn it into a sellable product, with privacy and licensing constraints designed in.
Do we need a new data stack first?
Rarely. We build on your existing warehouse and BI investments, adding the semantic, conversational and delivery layers that make them consumable.
Next step
Make your data earn its keep
Tell us the decision your teams make blind — we'll build the data product that lights it up.