System as spec
The spec they read is the spec Dogsled compiles and runs: declarative YAML, versioned in your repo. Never a stale copy.
Dogsled
Data engineering, redesigned for agents. A toolkit for building production-grade data products with agents.
Leading data product teams build with Bobsled: ZoomInfo, Deutsche Börse Group, LSEG, Dun & Bradstreet, GlobalData, Lightcast, CARTO, Cotality, Facteus, MediaRadar, Babel Street, Uniphore, LinkUp, Aampe.
A shared foundation for agentic data engineering.
Build and manage your data products with a team of agents, without losing context, duplicating work, or sacrificing control.
Understand your data.
Bring sources, models, relationships, metrics, and business definitions into one versioned Blueprint. Your agent reads the same definitions Dogsled uses to validate and run the work.
Validate each change.
Check references, types, dependencies, and contracts before execution. The compiler turns your project into a plan you and your agent can inspect.
Keep the work running.
Schedule pipelines, save checkpoints, and retry failed steps. The managed runtime keeps workflows running after the agent session ends.
The agent harness for data engineering. Build a team of data agents you can actually trust.
Agents and applicationsBuilt on the harness
- Context FactoryBuild, verify, and ship context with every data product.
- Quality LineAgents in your pipelines, finding issues before your customers do.
- GTM AgentLive buying experiences that turn prospects into customers.
- + Build your ownOn the same context and controls
- Claude Code
- Codex
- Gemini
Cursor
Dogsled CloudManaged runtime
Runs the compiled plan and keeps it running after the agent session ends.
- Orchestration
- Scheduling
- Checkpoints and retries
- Credentials and permissions
- Observability
Dogsled CoreOpen core
One versioned definition of your data system: what it means, how it runs, and which records describe the same entity.
Define
Describe the models, metrics, contracts, and pipelines that make up your data system.
Validate
Check references, types, dependencies, and policies before execution.
Resolve
Match fragmented records into consistent companies, people, and relationships.
Your data sourcesConnected in place
- StructuredDatabases, ERP, CRM, applications
- Semi-structuredJSON, XML, logs, events, APIs
- UnstructuredFiles, documents, images, text
- Snowflake
- Databricks
- BigQuery
- Redshift
- Postgres
- AWS S3
- Azure Blob
Built for agentic data engineering. Infrastructure designed for the new way data engineers work.
Contracts, not prompts
Contracts, types, and policies are checked in the compiler, not requested in the prompt. Invalid changes fail before they run.
Durable runtimes
The runtime holds state, checkpoints, and schedules. Pipelines keep running after the session ends.
Work with your existing stack. One project across the tools you use.
Bring your coding agent
Use Claude Code, Codex, or another MCP client to read project context, propose changes, and inspect results.
Build on your stack
Use pre-built connectors for the data warehouses, databases, and object stores already in your stack.
Never get locked in
Your entire project lives in portable YAML, so it moves with you between agents, tools, and workflows.
Trusted by the world’s leading data product teams. From financial services to property intelligence and more.
More customer stories
“Our sales team could not run without Bobsled. We can now do more with our data in an afternoon than we used to do in a quarter, and it’s showing up in the pipeline.”
Matt TrockeHead of Product, GlobalData
“Bobsled has been an amazing partner for our AI and interoperability strategy. They've driven real wins for us as a business.”
Scott MorrisonDirector, Data-as-a-Service, ZoomInfo
Cotality
LinkUp
Part of Bobsled OS.
One harness for context, quality, and speed.
Agentic Data Products
Unified Distribution