AI knows everything.Except your company.At last, your enterprise AX is complete.

It can be installed on-premises. Neither your code nor the analysis output ever leaves your servers.

Access is managed per team.

We don't store the prompts, source fragments, or raw request/response bodies used in LLM calls. Logs keep only minimal information such as processing time and token usage. The LLM itself can run on your own infrastructure (AWS Bedrock, Azure OpenAI, and so on). When the contract ends, access is revoked and data is handled according to your policies.

Platty doesn’t invent answers. It finds them in the structure built from analyzing your entire codebase, and cites code evidence for every sentence. With no evidence, it answers “not confirmed.”

We won’t claim “everything works.” Instead we sort it out before we start. Standard languages and frameworks are supported out of the box. Your own shared modules and wrapper patterns are covered by extending the analysis rules during rollout. Proprietary frameworks that depart entirely from the standard are scoped separately. We hand you a document showing which bucket each item falls into before analysis begins.

There are. That’s why every link carries its source. Links confirmed by static analysis are proven from the code structure — you can trust them as-is. Links that static analysis couldn’t resolve and the LLM inferred are marked separately, and are promoted to confirmed once a human verifies them. Every answer shows you which kind of evidence it rests on.

A better model still won’t know your system — just as the smartest new hire can’t work without a handover. Platty doesn’t compete with models. It’s the layer that lets any model understand your company. The better models get, the more useful Platty becomes.

That’s exactly who we built it for. It joins dozens of repos into one map, whatever the language. The older the code, the fewer people who understand it — and the bigger the payoff.

That’s fine. Platty doesn’t start by trusting your docs. It starts from the code, scores the docs against it, and keeps only what holds up. Even with no docs at all, you still get an SSOT.

Engineers tend to like it first. The “how does this work?” interruptions stop. Onboarding and impact analysis get faster too.

Once your repos are connected, it takes 1–7 days. No need to tidy up docs in advance, and no other prep work.

Yes. Beyond your production database, you can connect data lakes and warehouses (BigQuery and others). Because the code vouches for what each table and field means, you can query data in plain language too.

We charge by the volume of code analyzed (LOC), never per seat. Every employee and every AI agent uses it at no extra cost. We cover the LLM costs too. Full details are on the Pricing page.

Organizations where no one knows the whole system any more: large enterprises with heavy legacy, organizations building systems alongside multiple partners, and startups that grew so fast their knowledge scattered.