Pongo
Reduce LLM Hallucinations by 80%
Listed in categories:
APIArtificial IntelligenceDeveloper Tools
Description
Reduce LLM Hallucinations by 80. Cut hallucinations for RAG workflows with just 1 line of code using our semantic filter. Pongo has made it incredibly easy to get accurate results when building RAG pipelines.
How to use Pongo?
Pongo sits right on top of your existing pipeline whether you use a vector database or Elasticsearch. Just send us your top 100-200 search results and we'll return the relevant results.
Core features of Pongo:
1️⃣
Semantic Filter for RAG Workflows
2️⃣
Utilizes Multiple State of the Art Semantic Similarity Models
3️⃣
Proprietary Ranking Algorithm
4️⃣
Production Ready
5️⃣
Lightning Fast
Why could be used Pongo?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Reduce LLM Hallucinations for RAG Workflows | ✅ | |
| # 2 | Improve Search Relevance in Existing Pipelines | ✅ | |
| # 3 | Ensure Consistent Latency for High Request Volumes | ✅ | |
Pricing of Pongo:
Develop
Free
500 free queries per month. We'll work with you to integrate Pongo.
Deploy
$60 per month
60K queries per month. Standard compute at $8 per additional 10k queries.
Lightning
$250 per month
350K queries per month. 60% faster compute at $12 per additional 10k queries.
Enterprise
Custom
Optional BYOC Deployment. Custom Models. 99.99% Uptime SLA.
Who developed Pongo?
Parsa Khazaeepoul, AI2 Startup Incubator. Pongo Technologies Inc, Seattle, WA, USA.