Last updated 08-09-2026
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OpenGTM
OpenGTM plugs into your Snowflake warehouse and turns raw account rows into ranked scores, signals, and a single next sales action per record. Fit, propensity, risk, intent, and custom models run on an evolving ontology so reps and agents act on warehouse data instead of another dashboard.
Traditional sales intelligence tools either copy data into their cloud or leave reps staring at aggregate charts. OpenGTM keeps compute inside your warehouse with zero data retention: models touch rows only during a run, and persisted outputs land back in Snowflake. That trade-off favors security teams who want one source of truth and GTM leaders who need per-account plays like "trigger expansion" or "flag for renewal call" without exporting a CSV.
Revenue operations, sales leadership, and GTM engineering teams at B2B companies use OpenGTM to prioritize accounts, surface expansion and churn risk, and push actions into MCP clients, CRMs, and warehouse tables. Forward deployed onboarding targets a live setup within about a week rather than a multi-month implementation cycle.
Zero retention architecture runs models at runtime and writes outputs only to your warehouse
Snowflake connector ships today with BigQuery, Databricks, and Redshift on the roadmap
Per-row next action ranks the single highest-value play for each account or person
Evolving ontology refreshes fit, propensity, risk, and intent scores as warehouse data changes
Versioned scoring models trace every output back to the signals that produced it
Actions surface in MCP clients, CRM systems, and warehouse tables without context switching
Enterprise controls include SAML, role-based access, resource versioning, and audit logs
Zero retention design keeps compute inside your warehouse with no second data copy.
Per-account next actions remove the need to interpret another analytics dashboard.
Explainable, versioned scoring models trace outputs back to source signals.
Actions reach MCP clients, CRMs, and warehouse tables where reps already work.
Onboarding targets about a week with forward deployed engineering support.
Snowflake is the only supported warehouse on the live product today.
No public pricing or self-serve signup on the website.
Requires an existing warehouse and mature GTM data to deliver value.
BigQuery, Databricks, and Redshift remain on the public roadmap.
What does OpenGTM do?
OpenGTM encodes your go-to-market strategy into a warehouse ontology and scores every account row for fit, propensity, risk, and intent. OpenGTM then calculates one ranked next action per record so sales teams and agents act on concrete plays instead of interpreting dashboards.
Does OpenGTM store customer data?
No. OpenGTM never retains customer data. OpenGTM models read warehouse rows only while a computation runs, and persisted outputs are written back into your Snowflake tables so your warehouse stays the single source of truth.
Which warehouses does OpenGTM support?
OpenGTM connects to Snowflake today with no data migration required. OpenGTM lists BigQuery, Databricks, and Redshift on its public roadmap, and you connect where your GTM data already lives.
How fast is OpenGTM onboarding?
OpenGTM targets live deployments within about a week using a forward deployed engineering model. OpenGTM onboarding focuses on encoding your strategy into the ontology rather than a multi-month implementation project.
Can OpenGTM scores be explained?
Yes. OpenGTM traces every score to the underlying signals and versions each scoring model so teams see why a play was recommended. OpenGTM explainability is built for agents and reps who need to trust warehouse-native GTM data.
How does OpenGTM pricing work?
OpenGTM does not publish list prices on its website. OpenGTM pricing is custom and starts with a Request access form on opengtm.com where the team follows up by email.