The full-stack
data platformfor humans + agents

Datachef is a full-stack data platform. It connects, explores, models, visualizes and orchestrates data from Salesforce, Marketo, HubSpot and other business platforms and databases — ETL, data lake, modeling, visualization, reverse ETL and AI-assisted analytics in a single product, run for you. There is no stack to assemble, no data engineers to hire and no infrastructure to run.

If any of the following are true:

• Your standard reports are insufficient
• You understand that some queries are impossible in source systems (see "Overcoming the limits of SOQL")
• Data is scattered across multiple platforms
• You do not have a dedicated data engineering team, or your data engineering team does not have enough capacity to support your needs.

Datachef helps you overcome reporting limits, combine data from multiple sources, and operationalize core data models and analytical pipelines.

Assembling it in-house means four or five tools — a warehouse, plus ingestion, transformation, orchestration, BI and reverse ETL — wired together and then operated. The tools are good; the work is in running them, and in the months that pass before the first question gets an answer.

Datachef does that job as one full-stack data platform, operated by engineers who already know Salesforce, Marketo, HubSpot and NetSuite, live in days or weeks, at roughly 5–10% of the in-house cost — and aimed at the business teams asking the questions.

No. Datachef takes the go-to-market domain — Salesforce, Marketo, HubSpot, NetSuite and the databases around them — and serves the business teams asking questions of it. Your warehouse keeps doing what it is good at, and the GTM workloads that would otherwise land on it, and on the people who run it, land here instead.

For a data team this usually shows up two ways: a shorter request queue, because business users answer their own questions against governed models, and a fixed annual cost for those workloads rather than consumption that moves with them.

No. Ask questions in natural language and Datachef writes the SQL, shows you the assumptions it made, and charts the result. If you do know SQL, the editor is a real one with autocomplete over everything you have synced — and there are none of the basic-reporting limits your source systems impose. Either way, your dedicated solution engineer is there to help.

Yes — that is the Integrate step. Modeled data flows back into Salesforce, Marketo and HubSpot, so lead scores, advanced segments and meaningful events land in the systems your team already works in rather than in a dashboard nobody opens. Reverse ETL is included on the Enterprise and Custom plans.

Share models across the org so every query, report and QBR deck tells the same story. Work lives in named tabs that stay private until you publish them to your workspace, and permissions control who can view or edit each model and report. A published chart travels with its analysis, so a reader sees the chart its author built rather than a bare table.

Datachef is sold as an annual platform license: $11,988 for Professional, $29,988 for Enterprise, and from $120,000 for Custom. Plans differ by workspaces, AI token allowance, support level, reverse ETL and private cloud deployment — the full breakdown is in pricing. Additional consulting hours with your solution engineer are $225 per hour, and a free trial is available before you commit.

Yes. Private cloud deployment into your own AWS, Google Cloud or Azure account is available on the Custom plan. Professional and Enterprise run on the managed Datachef platform.

Datachef is SOC 2 compliant, and the security controls and supporting documentation can be provided on request. Data stored on the platform is always encrypted at rest, and leading technology, cybersecurity and financial services firms trust Datachef to process customer and prospect PII.