TOD

TOD is an AI decision model that reads text and images, extracts facts, and picks next actions for assistants.

TOD is a universal decision model that sits in front of an existing LLM assistant. It reads text and images together with conversation history, policy, and task state to extract facts and rank available actions. Built on a 12-billion-parameter model with a compact 400-million-parameter encoder, it evaluates options without generating free text. When confident, it serves the turn directly and skips the parent LLM call; when uncertain, it defers the turn to the existing model. It supports inputs such as text, photos, screenshots, and scanned documents, and operates with flat per-decision pricing.

TOD at a glance

Best for: Software engineer, Product manager
Pricing: $0.30 per 1,000 decisions, $300 per million
Released: October 2026
Category: AI agent tool
Website: parseclab.ai

Key features

Reads text and images together
Extracts structured facts from unstructured input
Ranks and selects available actions
Applies a confidence gate for handoffs
Processes up to 48,000 tokens of context
Scores available actions in two steps

Use it for

Automating customer support decisions
Looking up orders and replacements
Selecting replies and write actions

Alternatives to TOD

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MM helper — It keeps choices in your hands with strict budget guards and clear text options.
Limma — It answers queries with complete sets and proof instead of partial search fragments.

All TOD alternatives