Your web data,built and runfor you

Build in-house when the job is small and stable. A handful of sources, a schema that won’t change much, engineers with room on the roadmap, and no real cost if a scraper breaks for a week. Plenty of teams run that setup well and should keep running it.

Managed makes sense when one of these is true:

• Source count is past what one or two engineers can watch. Maintenance load scales with the number of sources, not with volume.
• The sites fight back. Anti-bot measures, JavaScript rendering, rate limits, and layout changes turn a build project into a permanent one.
• Something downstream depends on the data arriving. A customer-facing product, a model retraining schedule, a research deliverable. Silent breakage stops being an engineering problem and becomes a business one.
• The schema is deep. Nested fields, entity resolution across sources, industry-specific rules that standard scraper output won’t give you.
• Your engineers were hired to build something else. Most data teams don’t want scraper maintenance as a permanent line item.

The build is rarely the problem. Keeping sources clean and current for years, through redesigns, blocks, and quiet failures, is what consumes a team.

Four stages.

Consultation. We go through the sources, the fields, the volume, and the delivery format. If the data doesn’t exist in a usable form anywhere, we tell you at this stage rather than after a contract. We also flag the sources that are harder than they look.

Proof of concept. We build against a subset of your real sources and deliver a sample against your schema. You evaluate it on your requirements, not on a demo dataset.

Evaluation. You review the sample and tell us what’s wrong. Field mappings usually change here, and that’s what the stage is for.

Managed extraction. The pipeline goes live on your schedule. We monitor it, repair it when sources change, and expand coverage as your requirements grow. Every delivery goes through QA before it reaches you, and accuracy holds at 99.7%.

There’s no handover where the pipeline becomes your problem. The team assigned at consultation stays with the account.

You own it. Everything we extract for you is yours. We don’t resell it, aggregate it into a shared dataset, or reuse it for another client, and that’s written into the contract.

On the data itself:

• You define the schema. Fields, formats, naming, transformations, and business rules are built to your specification.
• You set the sources and the schedule. Add sources, drop sources, change frequency.
• You choose delivery. CSV, JSON, XML, or whatever format your systems expect, pushed to an API endpoint, a cloud bucket, a webhook, or a direct download.

On-premise is available for environments where the data has to stay inside your own infrastructure.

Yes for delivery. No for self-serve scraping.

We can deliver your data through an API endpoint your systems call, or push it to a webhook, a cloud bucket, or directly into your database, CRM, ERP, or vector database.

What we don’t sell is a scraping API where you send a URL and get a page back. With that model you still own the hard parts: deciding what to crawl, writing the parsers, validating the output, and fixing it when a site changes. Forage AI exists to take those parts off your team. The API is how finished data reaches you. The product is the pipeline behind it.