PIPER

PIPER — Pipeline Ingestion, Processing & Engineering Robot. Your agentic data delivery partner — built to deliver data applications end to end, across ingestion, cleansing, data products, quality, reconciliation, and DevOps, following domain-driven and data product architectures.

What PIPER Can Do For You

PIPER delivers end-to-end data applications across the full data engineering lifecycle, from ingestion and processing to data product generation, quality, reconciliation, and automated DevOp, following domain-driven and data product architectures (or adapting to your own Data Architecture).

Data Ingestion & Cleansing

PIPER ingests data from any source system through a conversational, guided experience, profiling schemas, classifying data types, selecting ingestion strategies, and generating clean, validated datasets ready for downstream consumption.

Data Products Generation

PIPER generates domain-aligned data products following data product and domain-driven architectures, producing all required artefacts automatically, from DDLs and pipeline code to factory registration and workflow configuration, with zero manual coding.

Data Reconciliation

PIPER validates data integrity end to end, automatically reconciling row counts, partition structures, and transformation outputs across layers to ensure every dataset is consistent, complete, and trustworthy before reaching consumers.

Data Quality

PIPER embeds data quality checks at every stage of the pipeline, validating completeness, accuracy, consistency, and SCD integrity before any data is committed — so quality is guaranteed by construction, not inspected after the fact.

DevOps & Engineering Standards

PIPER bakes DevOps practices and engineering standards into every generated artefact, enforcing naming conventions, Medallion architecture, CI/CD hooks, and pre-commit checks, so every pipeline is production-ready and compliant with your platform standards from day one.

Human-in-the-Loop by Design

At every critical decision point (strategy selection, configuration sign-off, quality validation) PIPER presents its recommendations for explicit human review before proceeding. AI speed with engineering oversight built in, not bolted on.

Integrate a new data source

Tell PIPER what source system you want to integrate. It configures the connection, profiles the source, and automatically creates all the required structures in your data architecture: DDLs, schemas, and registration, with no manual setup required.

Ingest and cleanse a new table

Tell PIPER what dataset you want to ingest: whether it's a database table, a file, an API feed, or any other format. It profiles the data, classifies it, recommends RAW and CLEAN strategies, and generates the full ingestion and cleansing pipeline, validated and committed, ready for downstream consumption.

Generate a data product

Describe the data product you need: its business purpose, the data it should expose, and the transformations required. PIPER interprets the requirements, applies the appropriate data modelling and reporting transformations, implements the business logic, and generates all required pipelines, DDLs, and artefacts automatically.

Deploy to your data platform environments

PIPER updates deployment scripts, manages platform configuration, deploys the data pipelines to the different environments and monitors the deployment across environments, ensuring every artefact follows your engineering standards and CI/CD practices from development to production.

Validate data quality and reconciliation

PIPER runs automated quality checks and reconciliation across every layer: validating row counts, completeness, consistency, and SCD integrity, ensuring data is trusted and accurate before it reaches any consumer or downstream system.

Update the data catalog automatically

Once a dataset or data product is delivered, PIPER automatically updates the data catalog with both business and technical metadata, including ownership, descriptions, data lineage, schemas, classifications, and quality indicators, keeping your catalog always current without any manual effort.

Who is it for

PIPER is built for data engineering teams that want industrialise the deliver high-quality data applications and trusted data products faster, with the right architecture, engineering standards, and governance built in from day one.

Data engineers

Stop writing boilerplate SQL, DDLs, and pipeline configs. Describe what you need in plain language and let PIPER handle the implementation, freeing you to focus on domain ownership, data product design, and the work that actually requires your expertise.

Data platform teams

Enforce naming conventions, DDL standards, Medallion architecture, and CI/CD practices across every pipeline, without manual review bottlenecks. PIPER bakes your platform standards into every generated artefact, so compliance is guaranteed by design, not policed after the fact.

Analytics & data product teams

Get trusted, domain-aligned data products to your consumers faster. PIPER's built-in two-run validation and automated quality checks mean data arrives clean, reconciled, and ready to use, eliminating the costly rework cycles that erode trust in your data platform.

PIPER

What PIPER Can Do For You

How it works

Who is it for