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Specialist agents. Tri-layer memory. Three autonomy levels. One orchestration system that understands why your pipelines exist — and keeps them running without you.
Agentic Pipeline Framework
The Agentic Pipeline Framework (APF) is Dagen's core architectural standard. Every pipeline is an intent-bearing, self-aware object — not a static script. APF defines how intent flows through the system, how agents collaborate, and how pipelines heal themselves.
Agent Infrastructure
With Dagen, you will have an army of dedicated specialist agents deployed at the right time for the right task. You can also create your own agent through the Agent Builder.
At the helm of it all is the Dagen super-agent that orchestrate them - routing work, resolving conflicts, and ensuring the full data pipeline lifecycle runs without issues.
Connects to any source via 500+ Airbyte connectors. Configures rate limits, retry logic, and incremental sync. Automatically adapts when source schemas or APIs change.
Generates dbt models, tests, and documentation aligned to your declared intent. Handles incremental logic, SCD patterns, and lineage documentation automatically.
Profiles source data, infers column semantics, maps business entities, and continuously updates the institutional knowledge base. Keeps your data catalog current automatically.
Designs medallion architecture — bronze raw ingestion, silver cleansed and conformed, gold business-ready KPIs — tailored to your declared use case and warehouse conventions.
Identifies and remediates quality issues — nulls, duplicates, type mismatches, referential integrity violations. Applies pipeline-specific rules derived from declared intent, not generic defaults.
Schedules, coordinates, and monitors execution across all pipeline layers. Integrates natively with Apache Airflow and dbt. Manages dependencies, retries, and SLA tracking.
Writes, optimizes, and debugs PySpark jobs for large-scale distributed workloads. Targets Databricks, Google Dataproc, Amazon EMR, Synapse Analytics, and Snowflake runtimes.
Creates realistic synthetic datasets mirroring production schemas and statistical distributions. Enables safe pipeline development, load testing, and regression validation without exposing real data.
Enriches pipelines with external data sources, public datasets, and real-time web content. Enables pipelines that incorporate first- and third-party signals for AI and RAG use cases.
Autonomy Levels
Calibrate how much autonomous decision-making Dagen exercises — per pipeline, per environment, or platform-wide. Change it any time as trust is established.
| Dimension | Guided | Semi-Autonomous | Autonomous |
|---|---|---|---|
| Best for | Teams new to agentic systems; high-sensitivity pipelines | Most production environments; established teams | Teams with high system trust; mature pipelines |
| Pipeline design | Agent proposes every decision, human approves | Agent decides routine steps; surfaces tradeoffs | Agent designs and deploys end-to-end |
| Schema drift | Alert + proposed fix, human applies | Auto-apply safe changes, flag breaking changes | Auto-remediate within guardrails |
| Quality failures | Alert + investigation report, human decides | Auto-quarantine low-risk; page on critical | Auto-remediate + reprocess; notify on exceptions only |
| Typical timeline | Day one | ~30 days | ~90 days |
Tri-Layer Memory
Every decision Dagen makes is stored, structured, and made available to future agents. Unlike stateless tools, Dagen's value grows over time — the system gets smarter with every pipeline built and every failure healed.
L1 — WORKING MEMORY
The current pipeline's full execution context: what's being built, which decisions have been made, what exceptions are in flight, and what the declared intent requires. Scoped to a single pipeline run.
L2 — EPISODIC MEMORY
A structured, queryable log of every pipeline event, schema change, quality issue, and remediation action. Enables accurate lineage tracking, impact analysis, and root-cause diagnosis across your entire data estate.
L3 — INSTITUTIONAL KNOWLEDGE
An organization-specific repository of best practices, naming conventions, data definitions, and tribal knowledge. Accumulates indefinitely. Informs every future agent decision. Survives team turnover.
Integrations
Dagen provides connections to PostgreSQL, MySQL, Oracle, Snowflake, BigQuery, Redshift, Databricks, Kafka, Salesforce, Azure Blob Storage, Amazon S3, Amazon Ozone, Apache Iceberg, Teradata, and Hive. You also have access to over 500 additional sources and APIs through the full Airbyte connector catalog.
PostgreSQL
MySQL
Oracle
Redshift
Snowflake
BigQuery
Kafka
Salesforce
Azure Blob
Amazon S3
Apache Iceberg
Hive
Teradata
Databricks
Asana
Tableau
Jira
HubSpot
Slack
Zendesk
QuickBooks
Looker
Notion
Stripe
Shopify
Airtable
Facebook
SharePoint
OneDrive
Twilio
NetSuite
Hugging Face
Google Drive
Zoom
MS Teams
Instagram
Gmail
Datadog
Okta
Block
Couchbase
Workday
Greenhouse
Google AdsEnterprise Features and Benefits
Dagen's extensive list of security, collaboration, governance, and observability features makes it suitable for enterprise teams looking to upgrade to leading edge infrastructure for the age of AI.
Try Dagen free or book a guided walkthrough with our team.
