Classer - High-performance AI classification

High-performance<br>AI classification<br>Beats GPT-5.4 accuracy · up to 100x cheaper · real-time latency<br>No prompt engineeringNo training required

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Classify

Copy Docs for AIsvg]:px-4 px-8">View Docs<br>Built for our own apps. Now open to everyone.

The Problem<br>You're overpaying for most AI tasks<br>You need to sort a support ticket. Detect spam. Route a phone call. Tag a product image. So you:<br>Iterate Prompts<br>Rewrite "be accurate" 47 ways until the model stops making things up.

Debug Schema Violations<br>Catch the 15% of responses that ignore your output format.

Face the Bill<br>Watch costs explode when you scale past demo.

It works. But it's slow, expensive, and embarrassingly over-engineered for a task that should take milliseconds.

The Solution<br>A dedicated engine for classification at scale<br>We stripped away the "chat" and let the intelligence focus on: turning messy data into accurate labels.<br>No more prompt engineering.<br>Provide your labels and let the engine auto-calibrate. No "Act as" fluff, no manual tweaking.

Zero schema violations.<br>Pure classification means zero hallucinations. Get the right format, every single time.

10x lower overhead.<br>Scale without the "LLM tax." Built for high-volume apps where speed and margins matter.

It's precise. It's predictable. It's the specialized infrastructure for the 90% of AI tasks that don't need a chat interface.

Comparison<br>How we compare to General-Purpose LLMs<br>FeatureClasserGeneralist (GPT-5 / Claude)Primary GoalHigh-speed classificationHuman-like conversationSetup60-second "Zero-shot"Weeks of prompt engineeringDeveloper CostLow. Non-technical "Correct" loop.High. Senior devs babysitting prompts.LatencyDeterministic (Variable (Seconds)Reliability100% Valid Outputs15% Schema violationsCost$ (Input tokens)$$$ (Input + Reasoning tokens)<br>Primary Goal<br>Classer: High-speed classification<br>LLM: Human-like conversation

Setup<br>Classer: 60-second "Zero-shot"<br>LLM: Weeks of prompt engineering

Developer Cost<br>Classer: Low. Non-technical "Correct" loop.<br>LLM: High. Senior devs babysitting prompts.

Latency<br>Classer: Deterministic (LLM: Variable (Seconds)

Reliability<br>Classer: 100% Valid Outputs<br>LLM: 15% Schema violations

Cost<br>Classer: $ (Input tokens)<br>LLM: $$$ (Input + Reasoning tokens)

Benchmarks<br>Tested on 33 public datasets<br>Classer beats GPT-5.4-mini on the top classification benchmarks — with zero training data.<br>Average<br>75.8%<br>Classer

vs<br>Average<br>67.7%<br>GPT-5.4-mini

DatasetClasserGPT-5.4-miniLexGLUE ECtHRlegal63.0%15.6%Financial PhraseBanksentiment69.8%24.1%LexGLUE Unfair-ToSlegal58.5%24.9%LexGLUE SCOTUSlegal70.0%44.5%App Reviewssentiment65.0%40.5%Sarcasm Detectionpragmatics76.0%58.0%RumourEvalmisinformation84.5%71.0%TREC Questionintent94.5%81.5%SMS Spammoderation97.0%90.5%<br>See all 33 benchmarks<br>svg]:px-4 bg-slate-900 text-white hover:bg-slate-800" href="/dashboard">Explore Platform

The Journey<br>Start in 60 seconds. Improve without ML engineers.

Zero-shot<br>Just pass your labels. It works out of the box.

Monitor<br>See every prediction in your console. Inspect confidence scores. Spot edge cases.

Correct<br>Add class descriptions. Label a few examples, or let a high-reasoning LLM do it automatically.

Auto-improve<br>Enable auto-calibration. The...