Semantic Deduplication + API Cache + User Behavior Detection. Self-learning technology with configurable thresholds. No GPU required. Patent pending.
Enterprise-grade deduplication technology that learns and improves automatically
Automatically discovers synonyms and patterns from your data. No training required.
Configurable thresholds ensure zero false positives when needed.
☁️ API: 50-400 q/s | 🖥️ Local: 3,000+ q/s. No GPU required.
Three USPTO patents pending. Licensed technology for your competitive advantage.
51% storage reduction verified on 50,000+ real-world queries.
Simple Python API. Works with any existing infrastructure.
Every query runs through all 3 engines. One API key. One unified response. Maximum value.
Each query returns: DEDUP_STATUS (UNIQUE/DUPLICATE) + CACHE_STATUS (MASTER/MERGE) + BEHAVIOR (SAFE/TOXIC + Action)
Clean LLM training data & databases. Remove exact, near, and semantic duplicates. Returns UNIQUE/MASTER or DUPLICATE/MERGE with 51%+ storage savings.
Cache AI responses semantically. "How to reset password" and "Change my password" return same cached response. 40-60% cost savings.
Real-time toxicity detection. Returns SAFE/TOXIC level + recommended action (BAN/WARN/MONITOR). Spam & abuse pattern detection.
Fine-tune thresholds and learning behavior per product
Configure how strict the matching should be. Lower threshold = more duplicates found. Higher = more precision.
Control how the system learns and what data it compares against. API learns words, synonyms, acronyms, and typos automatically.
The API automatically learns from every run and gets smarter over time
Reduce storage costs, improve moderation, and enhance user experience with self-learning deduplication
Problem: 50-60% of support tickets are duplicates. "App crashed", "Can't login", "Lost my data" repeated thousands of times.
Problem: Millions of messages daily. Spam, toxic messages, and repeated content flood platforms.
Problem: Same bug reported 100+ times with slightly different wording. "App crashes on startup" vs "Crashes when I launch".
Problem: Product descriptions, FAQ entries, and help articles have duplicates. Localization multiplies storage costs.
Problem: Event logs, user actions, and telemetry generate massive duplicate data. "User clicked button X" logged millions of times.
Problem: User reviews, comments, and forum posts have duplicates. Spam and repeated content clutter platforms.
Everything you need to integrate Hiwosy™ into your systems
Complete API reference with endpoints, code examples in Python, JavaScript, PHP, and cURL. Error codes, rate limits, and authentication guide.
Beyond REST API: Excel/Google Sheets extensions, Discord/Slack bots, Python/npm packages, CLI tools, browser extensions, and more.
From semantic deduplication to Semantic Operating System. LLM integration, RAG enhancement, autonomous learning, and the future of computing.
Honest comparison: different tools solve different problems
Purpose: File compression
Reduces file sizes by finding repeated byte patterns. Excellent for what it does - but it doesn't understand content meaning.
Purpose: Near-duplicate detection
Google's algorithm for finding similar documents based on word frequencies. Great for same-word duplicates, but misses synonyms.
Purpose: Semantic deduplication
Understands meaning, not just words. "Reset password" and "change password" are the same intent - we catch that.
| Capability | gzip | SimHash | Hiwosy™ |
|---|---|---|---|
| Primary Purpose | File compression | Near-duplicate detection | Semantic deduplication |
| Exact duplicates | ✓ (same bytes) | ✓ | ✓ |
| Same words, different order | ✗ | ✓ | ✓ |
| "reset" ↔ "change" | ✗ | ✗ | ✓ Synonym match |
| "How do I" ↔ "I want to" | ✗ | ✗ | ✓ Pattern match |
| Typo handling ("passowrd") | ✗ | ⚠️ Limited | ✓ |
| Self-learning vocabulary | ✗ | ✗ | ✓ |
| Typical dedup rate on support data | ~5-8% | ~20-30% | 50-65% |
gzip and SimHash are excellent tools for their intended purposes. We're not replacing them - we're solving a different problem they can't address: semantic equivalence.
If you need file compression → use gzip. If you need web-crawling deduplication → SimHash is proven at scale (Google uses it).
If you need to catch "reset password" and "change password" as the same query → that's where Hiwosy™ shines.
SimHash metrics: Penn State study (F-score 0.91, precision 0.94, recall 0.88 at k=3) • Source
Send us up to 1,000 sample queries and receive a detailed report showing potential storage savings.
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Get comprehensive metrics and recommendations.
Email us a CSV or JSON file with up to 1,000 sample queries (support tickets, chat messages, etc.)
We run your data through Hiwosy™ deduplication engine using our patented algorithm
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If results look good, we'll schedule a call to discuss pilot project or integration options
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