Small models guard every data hop between my agents — here's why

Description and use

Small models guard every data hop between agents, filtering, classifying, and re‑ranking information to prevent PII leaks and irrelevant data transfer.

Problem

Agent frameworks often miss guarding data transfers between agents, leading to potential leaks of sensitive information during memory writes, recalls, and handoffs.

Outcome

By inserting lightweight decision models at every internal data hop, AladdinAI prevents accidental leakage of sensitive or irrelevant information between agents and into memory, enhancing privacy without incurring the cost of large LLM calls.

Workflow

• 1. Agent delegates work → Handoff filter checks context and strips disallowed content using nvidia/llama-3.1-nemoguard-8b-topic-control.
• 2. Agent writes to memory → Memory write classifier decides persistence and screens for PII with the same NemoGuard model.
• 3. Memory recall → Recall reranker reorders results by semantic relevance using meta/llama-3.2-3b-instruct.
• 4. Decisions are logged and viewable per gate; memory is split private/shared to enforce boundaries.

Evidence

Each of these is toggleable per-agent, each logs its decisions (there's a "recent decisions" view per gate), and memory itself is split private/shared so agents don't leak facts across boundaries that were never meant to cross.

Source