# Tell us how you want your documents parsed > Custom Processors turn plain-language instructions and a few examples into a processor that parses your documents exactly the way you need. - Canonical: https://www.datalab.to/blog/custom-processors - Published: 2026-07-07 - Authors: Vanessa Chan We're excited to announce that **Custom Processors** are now available. Every document parsing tool eventually runs into the same wall: no two teams want their documents parsed the same way. One team needs bullet hierarchy preserved across a 40-page list. Another needs font and color carried into the HTML. A third needs the line items to actually add up to the total. Our state-of-the-art models handle the common case well, but that's not always representative of every unique situation. For a while we tried to close that gap with flags. Skip headers and footers. Custom prompts for image descriptions. Merge these tables, split those. Every new customer edge case became another toggle, and the surface kept growing. Custom Processors are the answer. Instead of hunting for the right combination of flags, you tell us how you want your documents parsed in plain instructions, and give us a few representative examples. We build a processor that does exactly that, making accurate, targeted modifications using custom models to our base [Convert](/platform/processors/convert) output. It's the experience of training your own model for your data, without the months of labeling. ## How it works You have two paths: - **Start from a template.** We've published processors for the most common needs — schema extraction, cleaned HTML, table normalization, and more. Pick one and run it today. - **Bring your own documents.** Send us a sample plus a description of your desired output, and we'll design a processor tailored to your data, evaluate its outputs with you, and refine it as we learn your workflow. Example of a custom processor to tag handwriting *Example of a [custom processor to tag handwriting](/app/pipelines/templates/handwriting-detection).* ## When does a custom processor make sense? A good litmus test is to ask yourself: How much customization or transformation is required on my data? - **Objective, predictable output transformations:** if the change you need follows a clear, deterministic pattern, our recommended solution is a static transformation script. - **Subjective output tuning:** if you need the output shaped to a judgment call (e.g., a house style, a style guide, a consistent treatment that doesn't have one objectively "correct" answer), then a custom processor is a strong fit, even when your input is perfectly predictable. As an example of the latter, one of our beta customers uses a custom processor to make sure image descriptions generated for construction documents follow a specific style guide. The input is consistent, but the desired output is subjective; doing it themselves would also involve running it through an LLM. Another factor to consider is how much modification you need. If you're scanning pages to pull a few numbers and a stray line break doesn't matter, a general parse makes sense. However, we've come across many cases where accuracy is load-bearing. In areas like compliance, legal, healthcare, and financial reconciliation, even one misread line or transposition error has a real downstream cost, which is where a custom processor is most valuable. ## What teams are doing with it We ran a beta with a few customers, where we looked for genuinely hard use cases to challenge the system. A few examples: - Long documents with complex, multi-page lists, that needed bullet hierarchy to stay consistent as those lists spilled across page breaks. - Color and font information that carried through into the HTML output. - Tables that needed to be merged and split to match their custom downstream schema. - Extracted values that needed to reconcile — line items that summed to the stated total. These represent real customer examples of specific, load-bearing details that make parsing more powerful in a real pipeline. Custom Processors let you specify them once instead of maintaining a pile of workarounds. ## Get started Our free tier includes one custom processor creation per month. Our Team plan offers four custom processor creations per month (then $5 for any additional creations). Using a custom processor is billed at an additional $20 per 1000 pages. Browse the [template gallery](/app/pipelines/templates) to self-serve a processor now, or reach out to [support@datalab.to](mailto:support@datalab.to) if you have a complex use case you'd like us to build around. If you've ever hit a wall with edge cases, inconsistent formats, or custom output needs, this is for you.