AI Aggregators: The Silent Risk in Your Work Tools

AI aggregator platforms emerged as a convenient solution: a single dashboard to access ChatGPT, Claude, Gemini and dozens of other models. But this convenience comes at a price many companies haven't yet calculated. ## What are AI aggregators? They are intermediary services that centralize access to multiple language models. Instead of contracting each API separately, users pay a subscription and access everything in one place. Examples include platforms like Poe, Merlin, and dozens of lesser-known services. ## Where is the risk? The problem lies in what happens to your data between you and the AI model. When you use ChatGPT directly, the relationship is clear: your data goes to OpenAI. When using an aggregator, your data passes through the aggregator's server before reaching the model — and this intermediary may: - Store all your conversations and uploaded files - Sell anonymized data for proprietary model training - Lack a clear or auditable privacy policy - Become a breach target due to its extremely valuable data pool ## How to evaluate an aggregator safely Before using any AI aggregator platform in a corporate environment, verify: 1. Data retention policy: how long are conversations stored? 2. Data usage: are they used to train proprietary models? 3. Certifications: do they have SOC 2, ISO 27001 or equivalent? 4. Server location: where is data stored? 5. Right to deletion: can you request complete data removal? ## Practical recommendations For corporate use, always prefer direct APIs from providers with signed Data Processing Agreements (DPA). Establish AI usage policies for your team and monitor which tools are being used. The risk of intellectual property leakage through unaudited aggregators is real and growing.