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Product

The governed decision layer for warehouse, product, and revenue data.

InfoKece unifies fragmented warehouse, product, and revenue sources into one semantic surface with sub-second queries, column-level lineage, and audit-ready row access — included in every plan.

Book a Demo → See it on your data →
In production at
  • Plaid
  • Notion
  • Ramp
  • Calendly
  • Segment
  • Stripe
app.infokece.com / metrics / revenue_daily
MetricDefinitionOwnerStatus
Net RevenueStripe − refundsFinance✓ Resolved
Active UsersLogged in ≤ 30dProduct✓ Resolved
Magic Number(Net New ARR × 4) / S&M spendGrowth! Pending
Gross Margin1 − COGS / RevenueFinance✓ Resolved
Query latency: 410 ms Lineage: 14 columns traced
140+ sources
  • Snowflake
  • BigQuery
  • Databricks
  • Postgres
  • Salesforce
  • Stripe
  • HubSpot
  • Segment
InfoKece semantic layer
  • Metric definitions
  • Row-access policies
  • Column-level lineage
40+ destinations
  • Slack
  • Web app
  • Reverse-ETL
  • Public API
  • Embedded
  • PDF
Your warehouse (kept)

InfoKece sits on top of your warehouse. It never replaces it.

Architecture

One semantic layer over your warehouse — not a replacement for it.

InfoKece reads from Snowflake, BigQuery, Databricks, Postgres, and 136 other sources through native connectors that refresh in under 90 seconds. It normalizes them into a single governed metric surface — then writes insights back out through an open API and reverse-ETL to 40+ destinations.

  • Read-only by default. No data movement, no shadow copies, no vendor lock-in.
  • Open API. Every metric, every dashboard, every row-access policy is reachable via REST.
  • 99.987% public uptime across the last 24 months.
See connector coverage →
Semantic metric layer

One definition per metric, enforced across finance, product, and growth.

Our patent-pending semantic engine auto-resolves 92% of metric definition conflicts between teams — so the number in the board deck matches the number in the dashboard matches the number in the warehouse.

How it works

A semantic graph that knows who owns what.

Every metric, dimension, and join is declared once — with an owner, a definition, a freshness contract, and a tested SQL implementation. The layer composes them into governed answers.

  • Declarative YAML or visual editor
  • Auto-detection of metric conflicts
  • Versioned, code-reviewed changes
Conflict resolution

92% of conflicts resolved automatically.

The layer inspects overlapping definitions across finance, product, and growth teams and proposes a canonical version — with diff, owners, and rationale attached.

Governance

Definitions are code, not folklore.

Every metric ships with a SQL implementation, a description, an owner, and a CI check. Broken definitions fail the deploy before they ever reach a dashboard.

Spreadsheet killer

Kill the “which number is right?” meeting.

Replace the six versions of the same metric floating in Notion, Sheets, and Looker with one governed source that everyone reads from.

Lineage & access

Audit-ready lineage and row-level access, in every plan including free.

Every dashboard, every metric, every value is traceable back to the source column it was derived from. Every query is filtered by row-access policies evaluated at the engine layer — not bolted on in the visualization tool.

  1. Column-level lineage. Click any number on a dashboard and see the upstream tables, the transformation code, and the downstream consumers.
  2. Row-access policies. Authored once, enforced everywhere — on dashboards, on the API, on embedded charts.
  3. Audit log. Every query, every export, every policy change is logged with user, timestamp, and dataset scope.
  4. Compliance, shipped. SOC 2 Type II, HIPAA, and ISO 27001 certified — with documentation your security team can hand to procurement.
Book a Demo →
Benchmarks

Benchmarked, not promised: the numbers behind the decision layer.

410ms

Avg. query response on billion-row fact tables

GigaOm, March 2024

8.4×

Faster time-to-insight vs. legacy BI

Across 1,100+ deployments since 2019

99.987%

Public uptime, last 24 months

status.infokece.com

92%

Metric conflicts auto-resolved

Internal benchmark, Q1 2024

Integrations

140+ native sources, open API, reverse-ETL to 40+ destinations.

Whether your team lives in the warehouse, the CRM, or the product analytics tool, InfoKece connects to it — and writes insights back to the systems where work actually happens.

Warehouses & databases

Read from where your data already lives.

  • Snowflake
  • BigQuery
  • Databricks
  • Postgres
  • Redshift
  • Snowflake
  • MySQL
  • MongoDB

Refresh in < 90 seconds. Read-only by default.

SaaS & product

Plug into the systems your operators use.

  • Salesforce
  • HubSpot
  • Stripe
  • Segment
  • Mixpanel
  • Zendesk
  • Intercom
  • Linear

140+ sources, native — no Airflow required.

Open API

Every metric is a REST endpoint.

  • GET /metrics
  • POST /queries
  • GET /lineage/:metric
  • POST /exports
  • Webhooks
  • OAuth + service tokens

Versioned, documented, and stable.

Reverse-ETL

Write governed insights back to 40+ destinations.

  • Slack
  • Salesforce
  • HubSpot
  • Customer.io
  • Outreach
  • Webhooks
  • S3 / GCS
  • Snowflake

Triggers on metric thresholds, anomalies, or schedules.

Book a Demo → Read customer stories →