Waaru
Self-learning AI

Gets smarter every week, without a retraining session.

When a human agent resolves a conversation the AI couldn't, Waaru indexes that resolution and uses it as authoritative context the next time the same intent appears. The AI handles the same question alone next time. Deflection compounds without manual retraining or fine-tuning.

No credit card. No commitment.

Chapter 01

Reads your business before the first message.

Point the AI at your website, upload PDFs, paste FAQs, or sync your Shopify catalog. Within minutes the Company Brain is indexed and the agent is replying with grounded answers — pricing, policies, product specs, business hours.

Chapter 02

Learns from every human resolution.

When the AI escalates and a human resolves the conversation, the resolution is captured, classified by intent, and indexed in the workspace's resolution store. The next time the same intent appears, the AI checks both the static Brain and the resolution store before replying.

Chapter 03

No retraining, no drift monitoring.

The underlying model is not fine-tuned — resolutions become retrieval-augmented context. No training run to schedule, no drift to monitor, instant rollback if a resolution turns out wrong. Workspace-isolated; resolutions never train shared models.

Chapter 04

Deflection that compounds.

Typical workspaces see deflection rates climb 1–2 percentage points per month for the first six months on the intents the team actively resolves. The compound effect: the AI handles 15–20% more conversations alone by month six.

FAQ

Questions worth answering.

No. Resolutions become retrieval-augmented context for the AI, not weights in a model. This means instant updates, instant rollback, and workspace isolation. No training run.

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