SearchBlox is bringing fast, contextual search and RAG to enterprises across ecommerce, customer service, knowledge management, legal, and digital platforms. To support AI at enterprise scale, companies need solutions that deliver speed, accuracy, and predictable costs.

SearchBlox SearchAI now integrates Inception’s Mercury dLLM, unlocking ultra-low-latency, cost-efficient GenAI at scale. This partnership provides SearchBlox customers sub-second GenAI responses even on enterprise workloads.

The Challenge: Speed and Cost at Production Scale

Enterprises deploying GenAI search face a fundamental tension: traditional autoregressive LLMs deliver quality but at latencies and costs that make real-time applications slow and expensive. For use cases like ecommerce product Q&A, customer support, or employee knowledge assistants, response time directly impacts satisfaction. 

SearchBlox needed a solution that could handle real-time queries without sacrificing accuracy or exploding infrastructure costs.

“Speed is now the defining differentiator for enterprise AI. Our partnership with Inception makes real-time GenAI a practical reality. Whether it’s customer support, compliance, risk, analytics, or e-commerce, every SearchAI customer benefits from sub-second intelligence across all of their data.”
- Timo Selvaraj, Chief Product Officer, SearchBlox

The Solution: Mercury Inside SearchAI's RAG Pipeline

Mercury made sense within SearchAI's pipeline for delivering fast, accurate inference at scale on unstructured text. Diffusion generation gives Mercury a parallel refinement path that enables enterprise search to run with consistent sub-second latency.

SearchBlox evaluated other lightweight models, but they carried higher latency or couldn't maintain quality across the range of tasks SearchAI handles. Mercury's architecture gives predictable performance even under bursty enterprise workloads, which is critical for customer-facing applications where inconsistent response times degrade user experience.

SearchBlox integrated Mercury into its SearchAI architecture as a model endpoint within their LLM abstraction. The integration required no refactoring or pipeline rewrites.

Mercury slots into the existing RAG pipeline alongside:

• Hybrid search

• Context builder and metadata enrichment

• Query rewriting

• SearchAI PreText NLP

• Vector and keyword fusion

• SmartFAQs

• Commerce search experiences

The integration preserves everything SearchAI customers already rely on while dramatically improving speed and cost.

Outcomes for Enterprise Search

Speed that scales. Mercury delivers sub-second inference even under heavy enterprise workloads. For SearchBlox customers, this means product Q&A, smart FAQs, and knowledge retrieval that feel instant, whether handling ten queries or ten thousand.

60 to 90% lower inference costs. Mercury reduced SearchBlox’s compute costs dramatically compared to using an autoregressive LLMs. Combined with SearchBlox's fixed-cost licensing model, enterprises get sustainable GenAI search economics.

Secure deployments. SearchAI customers can deploy Mercury on AWS Bedrock or Azure Foundry, ensuring that data never leaves their private cloud instance and that they inherit the full security, compliance, and governance frameworks of AWS or Azure.

Better quality through context. With SearchAI's RAG and metadata automation, Mercury gains higher grounding accuracy, better domain-aware summarization, personalized output for each user and workflow, multilingual support, and higher tolerance for noisy enterprise data. The result is hyper-relevant responses in every interaction.

Use Cases Now Production-Ready

With Mercury powering SearchAI, enterprises can confidently deploy SearchBlox’s GenAI solutions across:

eCommerce: Faster product Q&A, instant comparison summaries, real-time personalization, intelligent search suggestions.

Customer Support: Instant smart answers, agent assist and summarization, knowledge retrieval with no lag, 24/7 multilingual support.

Enterprise Knowledge and RAG: Contract and policy summarization, compliance checks, legal Q&A, employee knowledge assistants.

Digital Experience Search: Lightning-fast site search, contextual recommendations, AI-powered content discovery.

Takeaway

Whether handling ecommerce queries, customer support, legal research, or knowledge management, the combination of SearchAI's RAG pipeline and Mercury's diffusion generation process turns GenAI search from a cost center into a competitive advantage.

The future of enterprise search is real-time, contextual, and cost-efficient. SearchBlox and Inception are delivering it today.

Visit the link below for details on SearchAI + Mercury Diffusion LLMs, and schedule a personalized demo.

https://www.searchblox.com/partners/searchai-and-inception-mercury-diffusion-models