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Why Shim Exists

LLMs hallucinate. They truncate JSON mid-stream. They wrap valid objects in markdown fences. They forget closing brackets. Your options:
  1. Retry → Expensive (0.002/retry×1000failures=0.002/retry × 1000 failures = 2/day)
  2. OutputFixingParser → Slow (waits for full output, 2-5s delay)
  3. Regex hacks → Brittle (breaks on nested objects)
Shim: Receive. Repair. Return. Sub-millisecond repair, <10ms API response.

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What Shim Does

Shim is a streaming reliability layer for LLM outputs. Route all your LLM traffic through Shim to get:
  • Real-time repair (token-by-token, no buffering)
  • Schema validation (type coercion, missing field detection)
  • Confidence scoring (high/medium/low, never silent corruption)
  • Zero data storage (privacy-first, GDPR compliant)

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How It Works

// Before: Broken JSON from LLM
const raw = '{"name": "John", "age": "30"'; // Missing closing brace

// After: Shim repairs it
const response = await fetch('https://api.shim.so/v1/repair', {
  method: 'POST',
  headers: { 'Authorization': 'Bearer sk_xxx' },
  body: JSON.stringify({ raw_output: raw })
});

const { repaired, metadata } = await response.json();
// repaired: { name: "John", age: 30 }
// metadata.confidence: "high"
// metadata.repairs_applied: ["closed_object_bracket", "type_coercion"]

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Key Features

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1. Streaming-First Architecture

Batch repair is a tool. Streaming repair is infrastructure. Shim repairs JSON token-by-token without buffering delays.

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2. Schema-Aware Repair

Provide a JSON Schema and Shim will:
  • Coerce types ("30" → 30)
  • Detect missing required fields
  • Remove extra fields (strict mode)
  • Validate nested objects

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3. Never Fails Silently

Every response includes:
  • Confidence score (high/medium/low)
  • Exact repairs applied
  • Warnings for risky changes
  • Errors for unrecoverable issues

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4. Zero Data Persistence

Shim never stores:
  • Raw LLM outputs
  • Repaired JSON
  • Field names or values
We only log metadata: repair types, confidence, latency.

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5. Performance

Sub-millisecond repair, edge-deployed globally:
MetricPerformance
Repair engine<0.1ms (P99: 0.03ms)
Total API latency5-15ms (including auth, logging, network)
KV lookup<1ms
Edge deployment330+ locations globally
200-500x faster than OutputFixingParser (which waits 2-5 seconds for full output).

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Who Uses Shim

Indie Developers: Building AI apps with LangChain/LlamaIndex
Startups: Shipping AI features to production
Enterprises: Deploying AI at scale with compliance requirements

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Next Steps

Quick Start

Get your first repair working in 5 minutes

API Reference

Complete API documentation

Demo

Try Shim without signing up

TypeScript SDK

Install the official SDK