Learn from real-world case studies, technical breakdowns, and proven strategies that power high-performing AI assistants at scale.
How to build conversational commerce for products that need consultation, not search. Includes constraint matching, dynamic chip generation, compatibility engines, and the metrics that separate working implementations from demos.
Product teams are adding memory to AI assistants to improve continuity and personalization. Memory is not a single feature but a layered system. Designed well, it lifts resolution and trust. Designed poorly, it creates drift, privacy risk and cost.
A battle-tested architecture for multilingual RAG: translate at the edges, reason in one base language, and protect entities throughout. Includes chunking strategies for CJK scripts, embedding model benchmarks, and the metrics that matter.
HoverBot has launched a public demo portal that lets buyers, product teams and developers test its website chat widget in realistic scenarios. The portal includes a central gallery and two industry demos showcasing different use cases.
Many chatbots stall for the same reason. Unanswered questions build up and nothing changes. Learn how to capture every miss as a signal, turn real gaps into small updates, and run a weekly improvement loop that delivers results without bigger models.
Websites tend to embed chat in four patterns: a simple bubble, an inbox with history, a task-driven support bot, and a multi-tab hub. This guide explains where each pattern fits, what it does well, and the least you need to configure to run it reliably.
GPT-4o costs 15x more than GPT-4o-mini. Claude Opus costs 30x more than Haiku. The question is not which model to use. The question is which model to use for each request. A smart router cuts cost 70% while improving quality.
The hardest part is not the model, it is the human layer. Learn how to detect social intent, run guardrails, ground answers with retrieval, and use confidence gates to build chatbots that sound human, not robotic.
How AI chatbots have evolved from simple Q&A tools into full-service digital helpers that drive leads, handle onboarding, and boost revenue across nine different industries.
Why one-size-fits-all chatbots fall short and how modular skills add targeted, action-oriented capabilities like intent detection, promotional messaging, and CRM sync.
Seven production-tested patterns for handling personal data in LLM chatbots. Includes architecture diagrams, latency benchmarks, and the tradeoffs between stripping, masking, and vaulting PII.
How we handed HoverBot's repo to AI agents and transformed our engineering workflow with specialized ML, backend, frontend, DevOps, and QA agents.
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