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Mouse-1 vs Otto by Audos.com: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Mouse-1 and Otto by Audos.com — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Mouse-1 logo

Mouse-1

Mouse

Paid

Mouse-1 is a fast, low-cost decision model that plugs into agent harnesses to handle routing, gating and verification.

Key features

  • Decision Layer for Agents: Takes agent state and options and returns probabilities so the harness can route, gate and verify.
  • About 100 ms Latency: Answers faster than a chat model's first token.
  • Batch Decisions: One request answers up to 128 questions.
  • Prompt-Injection Resistance: Chooses only from supplied options; planted instructions changed 0% of decisions in vendor tests.
  • Zero Data Retention: Requests are scored and dropped, never stored or used for training.
  • Image and Document Classification: Handles content moderation, document routing and browser-state detection.

Best for

  • Agent Routing: Deciding which model or tool an agent should use next.
  • Action Gating: Approving or blocking risky agent actions cheaply.
  • Content Moderation: Classifying images or text as safe or unsafe.
  • Document Routing: Sending invoices, contracts and IDs to the right workflow.
  • Browser Agents: Detecting screen state such as login required or error.
  • Cost Reduction: Offloading small decisions from expensive frontier models.
View Mouse-1 details
O

Otto by Audos.com

surajshetty3416 / Otto (Frappe app)

Freemium

A Frappe application library that adds LLM capabilities (sessions, model management, queries) to Frappe apps.

Key features

  • Frappe Integration: Implements LLM capabilities as a Frappe application backed by DocTypes so model sessions and metadata are stored and managed in the Frappe framework.
  • Typed Library Interfaces: Exposes strongly typed modules (otto.lib.types and otto.llm.types) to build custom LLM features with clear type definitions and developer ergonomics.
  • Session Management: Provides session-based interaction support (OttoSession) allowing multi-turn conversations and continued context across requests while warning against directly coupling to internal DocType internals.
  • Quick One-off Queries: Offers utilities to perform single-shot operations such as document summarization or ad-hoc queries within a Frappe app.
  • Model Discovery & Creation: Includes tooling to discover available models and create new model configurations from within the application environment.
  • Otto Execution Workflows: Integrates with application-level execution flows so generated outputs and LLM interactions can be incorporated into business processes and custom features.
  • Exposes core LLM functionality as a library for Frappe apps
  • Session management (OttoSession backed by DocType)
  • Model management and discovery
  • Typed API definitions via otto.lib.types and otto.llm.types
  • Examples for one-off queries, session-based interactions, tool usage, and model creation
  • Integrated with Frappe DocTypes (not a standalone package)
  • Used internally for Otto Execution and application-level features
  • Repository documentation (README) with installation notes and usage examples

Best for

  • Document Summarization: Use Otto to add a one-click document summarization feature inside a Frappe app to generate concise summaries from uploaded documents.
  • Conversational Assistants: Build session-based chat assistants within ERP/CRM workflows that maintain context across interactions using OttoSession.
  • In-App Model Selection: Allow administrators to discover, configure, and switch between available LLM models for different app features (e.g., billing, support, knowledge base).
  • Workflow Automation: Embed LLM-driven execution steps into existing Frappe workflows to generate content, draft responses, or extract structured data from text.
  • Custom LLM Features: Developers create bespoke LLM-powered capabilities (e.g., guided form-filling, smart search, or code generation helpers) using the typed otto.lib interfaces.
  • Tool Integration: Combine Otto's LLM outputs with other Frappe DocTypes and business logic to automate tasks like ticket triage or knowledge base population.
  • Add conversational or session-based LLM features to Frappe applications
  • Build custom LLM-backed app features (summarization, generation, Q&A) inside Frappe
  • Create and manage LLM sessions and models from within a Frappe app
  • Instrument application-level execution flows that call LLMs (Otto Execution)
  • Prototype tool-usage patterns and model discovery workflows in Frappe
View Otto by Audos.com details