What questions should I put in an RFP for an internal app platform?

Summary

• The questions that matter most probe how close a platform's apps sit to your governed data and AI, and what you give up to connect them.
• Group your RFP into six areas: data access, governance and security, who can build, deployment and scale, observability, and cost.
• Ask whether apps can read governed data in place, without exporting a copy or standing up a second security model just for apps.
• Ask who can build on the platform: professional developers with an SDK and popular frameworks, and non-developers with a natural-language builder.
• Make each vendor demonstrate the answers on your own data and permissions, not a scripted demo, and ask how apps are monitored once in production.

What questions should I put in an RFP for an internal app platform?

A strong RFP should force each vendor to prove one thing above all: how close their apps sit to your governed data and AI, and what you trade away to get there. The questions that separate a real platform from a thin app host fall into six areas: data access, governance and security, who can build, deployment and scale, observability, and cost. Ask each vendor to demonstrate these with your own data and permissions rather than a canned demo. The platforms worth shortlisting let apps read governed data in place, inherit the access controls you already have, and deploy without a separate infrastructure project.

What is an internal app platform?

An internal app platform is the layer a company uses to build, deploy, secure, and operate its own applications: the data apps, dashboards, and AI tools employees use, as opposed to software sold to customers. For data and AI apps in particular, the platform's value depends less on which UI framework it supports and more on how directly and safely it reaches governed data, models, and agents. That is why the sharpest RFP questions are about proximity to data and unified governance, not cosmetic features.

Questions to put in your RFP

RFP question	What a strong answer looks like
How do apps reach governed data without making a copy?	Native, secure reads of governed tables and model endpoints in place, with no export step and no second copy to secure.
Does one governance model cover data, models, and the apps themselves?	Apps are first-class governed objects under the same catalog; access follows the permissions you already set.
Who can build on the platform?	Both professional developers, through an SDK and common frameworks, and non-developers, through a natural-language builder.
How are apps deployed and scaled?	Serverless, managed compute with no cluster to run; scales from one app to many; idle apps spin down.
How is access secured?	Single sign-on, OAuth and OIDC, user-level access drawn from the catalog, and built-in audit logging.
How do you monitor apps in production?	Built-in tracing and telemetry, support for open standards such as OpenTelemetry, and tooling to debug behavior.
How does the platform connect to AI and agents?	Native access to model serving, agents, and retrieval, without bolting on a separate vector store or session store.
What is the cost model, and does it scale to zero?	Usage-based, serverless economics so you pay for real use rather than idle infrastructure.
Does it run across our clouds under one governance model?	Consistent behavior and governance across major clouds, with enterprise compliance.

How Databricks Apps answers these questions

Databricks Apps is a generally available way to build and deploy internal data and AI applications that run where your governed data and AI already live. Its design answers the RFP areas above directly.
Data access and governance. Apps run inside the Databricks Data Intelligence Platform with native access to Unity Catalog data, model endpoints, and Lakebase, so there is no data movement and no separate security layer to build. Apps are governed as first-class objects, and access follows the Unity Catalog permissions you already configured. Databricks describes this in Introducing Databricks Apps.
Who can build. Professional developers use AppKit, a TypeScript SDK with built-in caching, telemetry, and retry logic, along with common frameworks such as Streamlit, Dash, Shiny, Gradio, and Flask, and Python or Node.js with React. Non-developers use Genie App Builder, which turns a plain-language description into a working app and is aware of your Unity Catalog tables, semantic definitions, and governance policies. This dual path is covered in enabling governed vibe coding for enterprise apps.
Deployment, security, and observability. Apps deploy on serverless, managed compute with no cluster to operate, across the major clouds, and can spin down when idle. Single sign-on, OAuth and OIDC, and audit logging come built in. For production monitoring, MLflow Tracing records app and agent behavior, telemetry can export through OpenTelemetry, and Genie Code helps debug. The general availability announcement covers deployment and security.

FAQs

Should the RFP ask about both low-code and pro-code building?

Yes. A platform that serves only one audience creates a gap: either developers wait on a tool built for analysts, or analysts wait on developers. Ask for a professional SDK and a natural-language builder that share the same governance.

What is the most overlooked RFP question?

How apps reach data. Many tools connect through an exported copy, which adds a second dataset to secure and keep fresh. Ask whether apps read governed data in place under one permission model.

How should we evaluate security in the RFP?

Ask for single sign-on, OAuth and OIDC, user-level access derived from your data catalog rather than app-specific roles, and audit logging that records who used each app and what data it touched.

How do we avoid platform lock-in across clouds?

Ask whether the platform runs across the clouds you use with the same governance and behavior, so an app built once does not need to be rebuilt or re-secured per cloud.