Every token your AI spends re-reading context is money you're burning on work that's already been done. Agents that remember don't repeat.
Every AI session re-reads the same documents, re-learns the same context, and reconstructs the same institutional knowledge. That's tokens spent on work already done.
More queries = more tokens = more cost. There's no efficiency gain from repeated interactions. Every session starts from zero.
Token costs are unpredictable when every query requires full context loading. Budget planning becomes guesswork.
Zdravo stores institutional knowledge in a structured memory graph. Agents retrieve exactly what they need in one query instead of re-reading entire document sets.
The more knowledge Zdravo captures, the less context agents need to load per query. Token costs decrease over time as your memory layer matures.
Track exactly how many tokens your memory layer saves. Show your finance team the ROI with concrete numbers, not estimates.
200 queries/day × 8,000 context tokens = 1.6M tokens/day
At $2.50/1M tokens (GPT-4o): $120/month
Every query loads full context from scratch. No memory. No reuse.
Same 200 queries/day × 3,200 context tokens = 640K tokens/day
At $2.50/1M tokens: $48/month
Agent retrieves relevant memories instead of re-loading context. 60% fewer tokens per query.
Example assumes 60% context reduction from persistent memory. Actual savings vary by use case. Zdravo Pro costs $19/mo — in this example, it pays for itself in under 5 days.
Free tier available. No credit card required.