Document intelligence that Behaves Like Software​

Built for ugly documentslayout driftsreal workflowstechnical teamsproduction use

Built for technical teams

Give developers the control they need to build document processing workflows that hold up beyond the demo.

Your Content Goes Here

Your Content Goes Here

Break free from classification first step

Create pipelines tailored to your workflow

Composable Pipelines

Build once, reuse everywhere—standardize extraction logic across teams and document types.

Config as Code

Define pipelines in readable, exportable config so teams can version, review, reuse, and ship document logic like software, not hidden UI state.

Transform Inputs

Preprocess and transform inputs at any level functions (deskew, cleanup, transforms) so downstream extraction is more accurate and stable.

Integrate Anywhere

Integrate with your stack without rebuilding everything around the tool.

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here

Your Content Goes Here
Rules meet flexibility

Pure AI extraction often performs well in demos but struggles once deployed in production. Outputs may vary between runs, models can fabricate fields, and updates quietly introduce drift. DataLime avoids this by pairing LLM flexibility with deterministic guardrails. Every extraction remains structured, validated against schemas, and backed by confidence signals and a clear audit trail.

Composable pipelines

Blend AI and non-AI methods in the same pipeline so you can handle messy documents without giving up control, predictability, or clean output.

Nested and Repeated Content Extraction

Handle repeated blocks, nested tables, and layout-heavy document structures without flattening everything into one brittle global grid. The evaluation notes explicitly mention nested tables, repeaters, and treating table surfaces as first-class extraction units.

Extensible Engine

Extend the system with custom logic where needed while keeping execution explicit, typed, and controlled instead of turning pipelines into script soup. The notes support JS and C# with typed contracts and safe extension boundaries.

Parameterized Execution

Write extraction logic once, then customize it with parameters. Prompts, field mappings, and thresholds can be injected at runtime, allowing the same pipeline to handle many document variations without duplicating configuration.