Mighty - Check customer files before people or AI act on them

Hey Product Hunt,

I’m Johnny, founder of Mighty.

It is getting harder to tell real customer submissions from manipulated ones.

A receipt can be generated.
A damage photo can be faked.
A PDF can hide white-on-white text that OCR reads but a person misses.
A document can contain instructions that steer an AI agent or summary.
OCR output can carry polluted text into a workflow.

Soon, the same class of problem will show up more often in voice and audio pipelines too.

The issue is not just “AI security.”

The issue is that more production workflows now depend on outside-submitted material: documents, images, receipts, claim photos, invoices, extracted text, generated summaries, and eventually audio. That material gets fed into OCR, IDP, AI agents, routing systems, support queues, claim workflows, payment reviews, and human reviewers.

If the input is bad, the output gets bad.

And once polluted material reaches the model or workflow context, it is much harder to recover. You are debugging summaries, decisions, audit trails, and downstream actions after the fact.

Mighty is built to sit before that happens.

Send Mighty customer-submitted files, images, OCR output, extracted text, or generated output through one endpoint. Mighty returns a practical workflow action: allow, review/warn, or block. We provide detailed evidence and audit logs.

What we wanted was simple but hard to find:

- Fast enough to run inline (milliseconds)
- Multimodal across text, images, and documents
- Deterministic enough for production routing
- Accurate enough to reduce noisy review
- Easy enough to test with one endpoint

- Suitable to use for older or recent models
- Useful before the input hits the AI model, OCR pipeline, reviewer queue, or automation step

A lot of teams try to solve this by asking an LLM to judge every input. That can work for some cases, but it is slow, inconsistent across models, expensive to benchmark, and often too late in the workflow. Mighty is purpose-built as the fast trust check before the material becomes context.

Our first wedge is P&C insurance because the examples are painfully concrete: fake claim photos, generated receipts, suspicious repair estimates, altered invoices, hidden text layers, polluted OCR output, and summaries that can steer adjusters or claim decisions.

But the broader problem applies to anyone building production workflows around customer or vendor submissions.

We also know teams may be cautious about sending sensitive material to another API. For sensitive workflows, teams can use a hashed-input mode so Mighty can scan without storing raw submitted content. For development and testing, plain-text dev keys make integration faster. If you need stricter control, we can discuss private cloud, bring-your-own-cloud, or on-prem deployment.

Audio scanning is entering close beta shortly after this launch.

For Product Hunt launch week, we’re offering 20% off your first month. More importantly, we’ll help teams test Mighty on one real workflow so you can see where an allow/warn/block check belongs.

I’d love feedback from builders and operators:

1. What outside-submitted material enters your workflow today?
2. Where would bad input create the most damage?
3. What evidence would make an allow/review/block decision useful enough to trust in production?

Thanks for checking out Mighty. Lets build a safer agentic world.

Great product!!

Does it do audio?