TOVANA uses your company's past cases and outcomes to make AI more accurate
Use your own past outcomes before the next decision.
Start with patterns your company has already seen.
Smaller models can start from a better place.
See the past outcomes and measured accuracy behind each prediction.
TOVANA sits behind the systems you already use and adds your company’s historical signal right before a decision.
Keep the workflows, agents and tools your team already uses.
If you already record cases and outcomes, you already have the raw material.
The answer appears inside the flow, where the decision is already happening.
Start with a key and a single call before changing anything else.
Your AI sees the case in front of it. TOVANA shows how similar cases ended before.
Example numbers only. Yours come from your own cases, with a measured score for how often they have been right.
73% of similar issues missed the release when they went a day without an owner. 3,914 past issues.
61% of similar changes were reverted or followed by a bug within seven days. 186 past commits.
88% of customers like this bought again within a week without a coupon. 24,900 customers.
69% of similar alerts became confirmed incidents. 1,420 past alerts.
“I haven't seen enough cases like this.”No percentage. No guess. The decision goes to a person.
The number is useful because you can see what it is standing on.
What usually happened next in cases like this.
How much company history is behind the answer.
How often this memory was right on cases it never trained on.
If there is not enough evidence, it says so instead of guessing.