Aviso

Overview

Aviso AI is an end-to-end AI revenue platform designed to assist sales and revenue operations teams. It offers agentic AI capabilities, forecasting, conversational intelligence, and unified RevOps functionalities within a single platform. The platform aims to streamline revenue activities and enhance productivity for go-to-market teams.

Key Features

• Agentic AI Workflows — Provides role-specific AI agents that deliver human-like revenue execution through contextual, real-time interactions to guide deals and engage prospects.
• GTM Agent Studio — Enables users to build, edit, and deploy AI agents without coding, utilizing pre-built blocks, chained actions, and adaptable workflows.
• Revenue Forecasting — Offers AI-enhanced forecasting analytics to provide a detailed view of business performance and predict revenue outcomes.
• Conversation Intelligence — Uncovers insights from sales calls, including how reps perform, buyer responses, and the impact of interactions on deal win probability.
• Relationship Intelligence — Moves beyond activity tracking to engage relevant buyers effectively.
• Pipeline Inspection — Provides tools for monitoring deal progression and identifying potential issues within the sales pipeline.
• Deal Acceleration — Offers guidance and tools to speed up the sales cycle and improve deal closure rates.

Who It's For

Aviso AI is designed for revenue teams, including sales professionals, revenue operations specialists, and sales leadership, across various company sizes. It targets organizations looking to consolidate their tech stack, improve forecasting accuracy, and enhance overall sales productivity through AI-driven insights and automation. The platform is suitable for enterprises and high-growth revenue teams seeking to scale their operations.

Notable Strengths

Aviso AI emphasizes its "Agentic AI" architecture, specifically MIKI, which is presented as an efficient alternative to traditional AI agents. The company claims MIKI achieves 90%+ correctness in answers and consumes 57% fewer tokens per query, leading to a 95%+ lower inference cost. This architecture is designed to provide complete business answers and next-best actions by combining LLMs with Large Quantitative Models (LQMs).