DataFramer

Use case - Security, IT, Compliance

Your cloud. Your keys.
Your data.

Keep your applications, agents, models, RAG pipelines, data, and workflows. DataFramer adds the operational layer for measurement, review, evaluation, and improvement.

It supports two ways to deploy: fully hosted or self-hosted with your data never leaving your account.

Where DataFramer sits in your data flow

Users & Applications Teams Business Systems Data Warehouse AI Agents & Observability DATAFRAMER Journey, Workflow & AI Intelligence 01 CONNECT & RECONSTRUCT One queryable history acrosspeople, systems, data and AI Includes the human + AI audit trail. 02 MEASURE OUTCOMES & FIND DRIVERS KPI → affected journeys → step→ driver Trace changes to people, systems,data, vendors or AI. 03 INTRODUCE & IMPROVE AI Finding → AI change →measured business result Introduce AI, or improve existing AIwith prompts, evals, training orfine-tuning. User System AI Human one case / journey timeline Cycle time ↑ 14% Affected 327 cases common pattern across affected journeys add / improve AI here Before vs after Outcome improved ✓ Human + AI Audit Trail across every step Revenue growth Lower operating cost Reduced human effort Better quality

Scroll to pan →

Sample Integrations

  • Databricks
  • Snowflake
  • PostHog
  • Segment
  • Claude Cowork
  • MCP
  • Amazon Redshift
  • LangSmith
  • Langfuse

Two ways to deploy

Both run the same application.

They differ only in where your data is processed and stored.

1. DataFramer-hosted

Your browserMCP client
DataFramer

Everything runs in DataFramer's cloud, scoped to your company. Model calls run on DataFramer credits, or your own provider keys if you add them under Settings → Keys. Nothing to deploy. Just sign up.

2. Customer-hosted

Your browserMCP client
DataFramer control planeYour data plane

Use this when your data cannot leave your own cloud. DataFramer keeps the control plane: the web app, job orchestration, and metadata. You run the data plane in your own cloud account, deployed with our Terraform module: the workers that process your data and the storage they use.

Customer-hosted, in detail
Your browser YOUR CLOUD ACCOUNT DATAFRAMER CONTROL PLANE Multi-tenant in our cloud. Does not hold your data. Web app & sign-in Orchestration API Schedules the jobs your workers pull Container image registry Versioned releases your cluster pulls Metadata & billing Names, statuses, storage pointers, usage DATAFRAMER DATA PLANE Deployed in your cloud account by Terraform. Gateway Communicates with your browser Workers Process your data Encrypted storage Your content under your own keys Sign-in, metadata Your content Poll for jobs, report status & usage Image pull LLM providers Your API keys Prompts & responses Langfuse or LangSmith Your existing project, or a new one Traces pulled in

Scroll to pan →

Every arrow crossing into the control plane starts on your side: your workers poll for jobs and pull images, rather than DataFramer reaching in. That is what "no inbound connections" means in practice.

Customer-hosted

What stays in your account.

Your content

Stays in your own cloud account, never DataFramer's.

No inbound connections

Every connection that crosses the boundary starts in your account or your browser.

Your provider keys

Model calls run on your own provider keys, not DataFramer's.

Same functionality

Customer-hosted runs the same product as DataFramer-hosted, not a stripped-down tier.

Compliance

SOC 2 Type II Certified
HIPAA Compliant

Keep your data exactly where it needs to be.

Start free in our cloud today, or talk to us about running the data plane in yours.

Try the live demo Talk to us