Frequently asked questions

What is Ragnerock?

Ragnerock is a platform for creating, operationalizing, and scaling AI-powered data processing workflows. Define how your data should be analyzed, run those workflows at scale, and have outputs flow directly into your existing data infrastructure.

What types of data can Ragnerock process?

Ragnerock works with a wide range of data formats: documents, spreadsheets, databases, dataframes, news feeds, websites, video, and more. Whether your inputs are structured or unstructured, Ragnerock can process them through AI-powered workflows.

Who uses Ragnerock?

Research and analytics teams at financial services firms, insurers, and other document-heavy industries. Our customers span trading, finance, insurance, healthcare, and legal.

How do I define data processing workflows?

Define JSON Schema specifications for the outputs you need: classifications, entities, metrics, sentiment, or custom fields. Ragnerock runs these workflows across your data and produces structured, queryable results.

How does Ragnerock integrate with my data infrastructure?

Ragnerock outputs flow directly into your existing systems. Connect to Snowflake, Databricks, PostgreSQL, or BigQuery for data lake integration. For analysis workflows, we integrate with JupyterLab and provide a Python SDK. Our REST API enables integration with any system.

Can I use my own AI provider?

Yes. With Bring Your Own AI (BYOAI), you can use your own API keys from OpenAI, Anthropic, Google, or xAI. This gives you control over costs, lets you leverage existing enterprise AI contracts, and helps meet data residency requirements.

How does Ragnerock handle data security and sovereignty?

Enterprise customers can use their own database (BYODB) and blob storage (BYOBS) for complete data sovereignty. All data is encrypted in transit and at rest, with role-based access control and full audit trails.

How does source traceability work?

Every piece of extracted data includes complete references back to the original source. When Ragnerock produces an insight, you can trace it to the exact input it came from. This is critical for auditing, compliance, and verification.

What's the notebook chat interface?

Unlike typical AI assistants that return only text, Ragnerock's notebook chat produces outputs that become programmatically accessible Python objects. Ask a question and get a DataFrame you can immediately use in your analysis. It bridges conversational exploration with data workflows.

Is there a free trial?

Yes. You can start with our free pay-as-you-go plan to explore Ragnerock's capabilities. New accounts start with 20 free credits. When you're ready for more power, including BYOAI, BYODB, and advanced team features, upgrade to an Enterprise subscription.