Validate, transform, sanitize, and review JSON for AI apps and APIs — with visual pipeline steps, diffs, and version history.
No black box — inspect every step before applying.
Modernize this payload: camelCase keys, dollars not cents, booleans instead of "yes/no".
{ // "email" removed "userId": "u_8842", "fullName": "Jane Doe", "isActive": true, "balance": 124.51}Built for the LLM JSON problem
Validate JSON before it reaches AI. Then sanitize and normalize the output before it enters your app.
Explore how it worksCatch shape errors, missing fields, and bad types upstream — before the model wastes a token.
Strip PII, internal notes, and audit metadata before the prompt ever leaves your stack.
Coerce strings, fix casing, drop hallucinated keys — every response lands in the shape your code expects.
What a pipeline actually does
{ "email": "user@example.com",// ❌ email removed "internalNote": "VIP",// ❌ internalNote removed "paid": "yes"// → paid normalized}{ "paid": true }Three saves: PII removed, internal fields removed, values normalized.
Catch bad JSON before AI sees it
Validate input upstream
Sanitize AI output before it breaks app
Strip + normalize downstream
See exactly what changed
Field-level diff
Build pipelines, not prompts
Reusable transforms
Run the same logic via API
OpenAPI contract
Workflow story
Workflow story
Mismatched keys, wrong types, fields you have to rename before anything downstream can use them.
Real utility steps the product can validate before you commit.
Open the draft in the editor, diff every field, then run. No black-box execution.
Why Forge Json
Turn unpredictable AI output into structured, reviewable pipelines.
AI output feels random
Prompts are hard to debug
No memory or change history
Deterministic pipelines with validated steps
Visual step-by-step flow you can inspect before run
Versioning and diff for every iteration
AI Draft gives you the first pass. The editor is where that draft becomes trustworthy.
AI suggests. You verify.
Compare changes side-by-side, inspect every field, and track every version.
Review original and transformed JSON together instead of trusting raw output.
Switch between structural tree navigation and raw text whenever the problem demands it.
See exactly what changed, including renamed fields, normalized values, and removed noise.
Every iteration stays traceable, so AI-assisted edits never become a black box.
Product depth
AI gets you a draft fast. The editor makes it trustworthy. The platform layer makes the workflow reusable, integrate-able, and durable across teams.
MCP-ready foundation
Forge Json is not promising an agent platform here. It already provides the contract layer: utility metadata, examples, and OpenAPI. AI Draft uses that contract today. MCP can use the same foundation later, while the editor remains the human review surface before anything runs.
A JSON pipeline is a sequence of steps that transforms, validates, and cleans JSON data before it is used in APIs or AI systems. Forge JSON lets you build these pipelines visually, inspect every step, and ensure consistent, reliable output.
Before sending data to AI models, JSON should be validated and sanitized to avoid leaking sensitive fields or breaking downstream logic. Forge JSON provides validation, transformation, and diff tools to ensure safe and predictable AI inputs and outputs.
Learn about LLM JSON reliabilityStart with the flow
Try a pipeline on your messy input. Or see how to make AI JSON safe end-to-end.