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Milliseconds.ai vs TheySaid 3.0: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Milliseconds.ai and TheySaid 3.0 — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Milliseconds.ai logo

Milliseconds.ai

CloudRaker

Freemium

A small decision model served over a REST API that returns typed labels, scores, spans, and JSON fields from text or images in milliseconds.

Key features

  • Typed Decision Endpoints: Eight purpose-built routes — yes-no, classify, classify-tree, rate, answer, extract, entities, and verify — each returning structured JSON rather than free text, so application code can branch on the result immediately.
  • Sub-Second Latency: A decision returns in about 90 milliseconds, answer calls in 0.3–0.9 seconds, and extraction in 2.5–3.5 seconds at medium detail, making the model usable inside request paths rather than background jobs.
  • Calibrated Probabilities: Responses include per-label probabilities and a confidence value, so near-ties surface as uncertainty your application can route to a human instead of acting on silently.
  • Schema-Driven Extraction: Send a JSON Schema and get back a filled object — up to five fields per extract call — ready for validation before writing to a record.
  • Image Input: Send JPEG, PNG, or WebP images up to 5 MB as bytes, a data URL, or base64, billed as a fixed token count set by the detail level you request, with no image storage retained.
  • Answer Spans with Offsets: The answer capability returns the exact text span plus start and end offsets, so an application can highlight where in the source the answer came from.
  • SDKs and CLI: Hand-written TypeScript (@cloudraker/milliseconds) and Python (cloudraker-milliseconds) SDKs plus a dm1 CLI, where label names, scale levels, and schemas flow into the result type so a misspelled label is a compile error.
  • Free Test Tier: Test keys carry 125 million free input tokens a month with no card required, at 30 requests and 500,000 input tokens per minute, shared across an organization.

Best for

  • Support Ticket Routing: Classifying inbound messages into billing, shipping, or technical queues and flagging urgent ones for faster response.
  • Invoice and Receipt Processing: Extracting invoice number, vendor, total, and currency from document text or images into validated fields before writing a record.
  • Content Moderation and Policy Checks: Verifying whether a return request, listing, or submission satisfies a written policy before it reaches a human reviewer.
  • Sentiment and Priority Scoring: Rating customer frustration on a defined scale to sort a support queue by how badly each thread needs attention.
  • Entity Recognition in Records: Pulling people, organizations, claim IDs, and dates out of free-text notes for search and record matching.
  • Agent Tool Calls: Giving an LLM agent a fast, cheap decision primitive for yes/no and classification steps that do not need a generative model.
View Milliseconds.ai details
TheySaid 3.0 logo

TheySaid 3.0

TheySaid

Freemium

Turn single-question surveys into real-time conversational surveys to boost engagement and surface richer insights.

Key features

  • Conversational Survey Conversion: Transforms single-question surveys into AI-driven multi-turn conversations that probe respondents with contextual follow-ups to gather richer qualitative data.
  • Real-time Engagement: Dynamically adapts follow-up prompts based on answers to keep respondents engaged and reduce drop-off during the survey experience.
  • Automated Insight Extraction: Aggregates and summarizes responses, surfaces recurring themes and sentiment, and highlights actionable findings for faster analysis.
  • Intelligent Question Generation: Generates clarifying and targeted follow-up questions tailored to each respondent’s answers to obtain deeper context and reasons.
  • Response Analytics Dashboard: Provides aggregated views, filters, and breakdowns (e.g., sentiment and themes) to help teams interpret results quickly.
  • Export & Integration: Enables exporting response data and integrating survey outputs with downstream analytics or research workflows for further analysis.
  • Conversational AI Surveys that adapt follow-up questions based on responses
  • AI Interviews to automate in-depth user interviews
  • AI Pulses and Polls for single-question feedback and follow-ups
  • Question recommendation and auto-generation from website content
  • Embedding and delivery via existing channels
  • AI-driven summarization of responses and insights
  • Convert single-question surveys into interactive, AI-driven conversations
  • Real-time capture of conversational survey responses
  • Smart conversational survey design to boost respondent engagement
  • Automated analysis and extraction of insights from conversational responses
  • Web-based survey creation and results dashboard

Best for

  • Converting NPS/CSAT single-question prompts into conversational flows to collect reasons, suggestions, and context behind scores for better actionability.
  • Market research that requires scalable qualitative feedback by turning short surveys into richer interviews to surface customer needs and motivations.
  • Customer support and feedback collection that triages issues via guided conversation and captures exact user language and sentiment for product teams.
  • Employee pulse and HR surveys that solicit candid explanations and suggestions while maintaining higher completion rates through conversational engagement.
  • Product discovery and usability testing to gather in-depth user reactions, feature requests, and pain points from compact, conversational surveys.
  • Collecting product and UX feedback via conversational surveys
  • Automating user interviews to surface deeper insights
  • Running NPS/CSAT/CES pulses with follow-up probing
  • Embedding surveys across websites and apps to increase engagement
  • Conducting user tests and polls with AI follow-ups to understand reasons
  • Customer feedback collection with richer qualitative responses
  • Market research using conversational probes to uncover insights
  • Product feedback and user experience surveys
  • NPS and satisfaction measurement with follow-up conversational context
  • Employee engagement and pulse surveys
View TheySaid 3.0 details