Solutions

Data solutions for every team

Whether you're building analytics infrastructure, real-time data products, or ML pipelines, Interlace provides the foundation you need.

Built for modern data challenges

From batch analytics to real-time ML features, Interlace adapts to your needs.

Analytics Engineering

Build semantic layers and metrics stores with version-controlled transformations. Replace fragmented SQL scripts with maintainable, testable models.

Unified metric definitionsSelf-documenting transformationsAutomatic dependency trackingIncremental computation

Example: Create curated datasets for BI tools with guaranteed data freshness and lineage.

Data Warehouse Modernization

Migrate from legacy ETL tools to a modern, code-first approach. Run locally on DuckDB, deploy to your production warehouse.

No vendor lock-inGit-based workflowsLocal developmentGradual migration

Example: Replace Informatica or SSIS with Python and SQL models that run anywhere.

Scheduled Data Products

Build data products with scheduled pipelines, API-triggered runs, and automatic dependency resolution.

Cron schedulingAPI triggersParallel executionChange detection

Example: Power dashboards and analytics features with fresh, scheduled data pipelines.

Data Integration

Unify data from multiple sources into consolidated views. Combine APIs, files, and databases with Python and SQL.

Multi-source joinsSchema evolutionData quality checksMerge strategies

Example: Combine CRM exports, API data, and database tables into unified datasets.

Business Analytics

Build analytics pipelines that transform raw data into curated datasets for BI tools and reporting.

Aggregate metricsDimensional modelingExport to CSV/ParquetLineage tracking

Example: Build product analytics and reporting pipelines with full data lineage.

ML Feature Engineering

Create reproducible feature pipelines that prepare training data with versioned, testable transformations.

Reproducible transformsSchema validationExport formatsIbis-powered SQL

Example: Build feature pipelines with consistent transformations across environments.

API Integration Pipelines

Integrate with production-only APIs (GitHub, Companies House, Ordnance Survey) and share source data across dev/staging/prod without re-fetching.

Source caching with TTLZero API calls in devRate limit friendlyShared source layer

Example: Fetch Companies House data weekly, cache it, and develop transformations against real data without hitting the API.

Multi-Environment Data Platforms

Build dev/staging/prod pipelines with shared source layers, zero-copy reads, and safe environment isolation.

Virtual environmentsAccess policiesFallback resolutionConfig overlays

Example: Develop locally with DuckDB reading shared sources, deploy to Snowflake in production — same models, different connections.

Built for any industry

Interlace provides the foundation for data infrastructure across industries.

Financial Services

Regulatory reporting, risk analytics, and fraud detection

Retail & E-commerce

Customer analytics, inventory optimization, personalization

Healthcare

Clinical analytics, patient journeys, compliance reporting

Technology

Product analytics, usage metrics, infrastructure monitoring

Flexible deployment patterns

Run Interlace wherever your data lives. From local development to cloud production, the same code runs everywhere.

Your infrastructure

Data never leaves your environment. Deploy on-prem or in your cloud VPC.

Dev to production

Develop with DuckDB, deploy to PostgreSQL or other ibis-supported backends.

Embedded analytics

Build DuckDB-powered analytics directly into your applications.

Deployment Options
Local Development
DuckDB Zero setup, instant feedback
Production
PostgreSQL DuckDB
Via Ibis (additional backends)
Snowflake BigQuery MySQL + more

Ready to simplify your data pipelines?

Get started with Interlace in minutes. Install, define your first model, and run.