You've already bought AI. What you can't buy is permission to use your most sensitive data with it.
Microsoft, OpenAI, Anthropic and Google sell you the models. None of them can make your customers, contracts, pricing and operations safe to use with AI. Maya is that permission layer.
Not another AI app. The layer underneath every AI app.
Maya is not a chatbot, an LLM, a model provider or an AI workspace. It is the infrastructure that makes enterprise data safe enough to use with all of them.
The data that creates the most value is the data you can't safely use
Three forces are converging at once — and together they turn your best data from an asset into a liability the moment AI touches it.
AI adoption is accelerating
Every team wants AI in the workflow — and each new use case reaches for more of your real business data.
Regulation is tightening
GDPR, the EU AI Act, DPDP and sector rules raise the bar on what may leave the organization, and when.
Knowledge is leaking outward
Sensitive business knowledge increasingly flows into external AI systems — often without visibility or control.
The result is a bottleneck every enterprise feels: AI projects held back by data restrictions can finally move forward — that is the outcome Maya delivers.
Not all data should take the same path
Internal AI can use most of your data. External AI should narrow as sensitivity rises. Maya turns that principle into an operational control — classifying and routing data so the right information reaches the right model, and nothing more.
AI applications help people use AI. Maya helps AI use your intelligence.
Copilot, ChatGPT, Claude, Gemini, Glean — they put AI in your team's hands. They take AI up to your data and stop where the risk begins. Maya carries it the rest of the way.
- Employee productivity
- Chat interfaces
- Generic reasoning
- Enterprise intelligence
- Cross-system context
- Controlled AI access
- Internal-first execution
AI applications provide reasoning. Maya provides context. Without context, AI stays generic.
Others solve one layer. Maya has all five in one.
Alone, each control is common. Together, in a single layer, they become the difference — and each turns into a business outcome, not a feature.
Prompt-level anonymization + re-identification
Sensitive elements are tokenized before transit and mapped back for authorized users.
Cross-system consistency
The same entity resolves to the same token across SAP, Oracle, files and prompts.
Zero data storage
AISafe retains nothing. There is no repository of your data to breach or hand over.
EU-native + air-gapped deployment
Deploy in your cloud, on-prem, or fully air-gapped for sovereign environments.
Granted patents (EPO + USPTO)
Patents protect Maya's Data Safe AI Transformations (DSAIT) — the core technology.
The empty quadrant
Map any competitor against all five and the overlap is empty. Almost nobody can claim every one.
Private AI controls where AI runs. Maya controls how your intelligence is used.
Self-hosted Llama, Azure OpenAI private, Prem AI — they keep the model in your walls. They do nothing about what it's allowed to know once your data is in the prompt.
Private AI protects infrastructure. Maya protects enterprise advantage.
Copilot, Langdock, DLP and governance solve a different problem
Copilot gives productivity. Langdock gives AI access. DLP gives blocking. Governance gives policy. Maya gives AI-safe access to the business knowledge those tools cannot safely use raw.
| Category | What it does | Where Maya is different |
|---|---|---|
| Copilot / ChatGPT Enterprise | AI productivity for employees | Makes your sensitive enterprise knowledge safe to use with it — and any other model. |
| Langdock | An AI workspace / multi-model access | The anonymization layer that sits underneath any model or workspace. Use them together. |
| Glean | Enterprise search / RAG assistant across your apps | Glean reads your data as-is to answer. Maya anonymizes it before use and re-identifies locally — so AI uses your context without exposing it. |
| Private AI | Prompt & text anonymization | Extends to databases, SAP, Oracle, files and apps — at enterprise-system scale. |
| DLP (Nightfall, Zscaler…) | Detects and stops sensitive data flows | DLP stops the use case. Maya transforms the data so the use case safely proceeds. |
| Governance / GRC (OneTrust, Purview…) | Describes and documents policy | Governance is policy; Maya is the technology that enforces it the moment data meets a model. |
Not an AI chat platform
Maya sits alongside the models you already use — it doesn't ask you to adopt yet another chat app.
Not just DLP
DLP detects and stops. Maya transforms — so the use case proceeds safely instead of being cut off.
Not a governance dashboard
Governance describes policy — OneTrust, Purview, Immuta and IBM watsonx tell you who should access what and keep the evidence you should retain. Maya is the technology that acts on it: it enforces the control, applies the anonymization, routes the data, selects the model and records the outcome — at the one moment that matters, when data meets a model. Governance tells you what should happen; Maya makes it happen.
Three layers of control
Governance describes these. Maya operationalizes them — enforced at the moment data meets a model.
Data controls
Classification, minimization, anonymization, access boundaries and retention logic.
Model controls
Approved model lists, capability routing, version awareness and fallback paths.
Outcome controls
Output validation, human review, escalation, evidence and continuous improvement.
One layer. A different reason to buy for every decision-maker.
The same platform answers the question each stakeholder is actually asking — in their own language.
Waiting is not neutral. The cost compounds on two sides at once.
Every month you delay, employees keep using unsanctioned AI while your regulated data stays off-limits to approved projects. That is a double loss — one you pay for in exposure and in missed advantage.
Uncontrolled usage rises
- Staff keep pasting real customer and contract data into consumer AI.
- You can't see it, log it, or govern it.
- Sensitive information leaves the organization uncontrolled.
High-value AI stays on hold
- Approved initiatives stall in security and privacy review.
- Your most valuable data stays unavailable to AI.
- AI keeps running on public information everyone else has too.
Trust, engineered in — and independently attested
Maya is a European privacy-engineering company built for regulated industries from the ground up. Privacy is designed into the architecture, not bolted on afterwards.
- ✓ISO 27001 & SOC 2 — independently attested security and confidentiality controls.
- ✓EPO + USPTO patents — for Data Safe AI Transformations (DSAIT).
- ✓Production, not pilots — live across Norway, Germany, Austria, Switzerland and Ireland.
- ✓Zero data storage — nothing retained, nothing to disclose.
Live production deployments across the EU/EEA
Granted patents — EPO and USPTO
of your data stored by AISafe
model-agnostic — bring any LLM
The questions that decide the evaluation
Why not simply use ChatGPT Enterprise, Copilot or Claude Enterprise?
Can Maya help us use data that is currently off-limits to AI?
Does Maya support agentic AI?
Does Maya store our prompts or data?
Can we deploy on-premises or air-gapped?
Will Maya reduce AI quality?
Does Maya create vendor lock-in?
Why spend on Maya instead of simply buying more Copilot or ChatGPT licences?
Why not build this ourselves?
Bring your hardest security or privacy objection.
Security, DPO, CFO and AI leaders welcome. Show us the AI use case you have in mind and see the five capabilities working together on your data.
Show us your AI use case →