cognitive search

Find Answers from Unstructured Data with Floatbot QnA - Cognitive Search

Leverage AI-Powered Cognitive QnA to enable your customers and employees to find answers from unstructured, diverse datasets - pdf, Word, knowledgebase, or website pages. It is powered by deep tech capabilities, such as unsupervised self-learning, NLP, semantic search, and fuzzy matching.


Advanced Solutions Powered by Floatbot QnA – Cognitive Search

Build AI Agent Assist
Build AI Agent Assist

Build an AI Agent Assist on top of Floatbot QnA (Cognitive Search) to help your human agents discover answers to customer queries. Solve customer issues faster, boost agent productivity, increase customer satisfaction (CSAT) scores, and reduce MTTR (Mean Time To Resolve).

Enable Customer Support

Deploy conversational AI Chatbots and Voicebots powered by cognitive search to automate customer support, helping customers to discover and access FAQs and information related to your products and services. Enable self-service, provide 24x7 customer support, and reduce support costs.

Enable Customer Support
Deploy Employee Assist
Deploy Employee Assist

Deploy Cognitive Search on top of enterprise search to enable your employees to discover and access relevant information accurately. Help new employees become comfortable with the organizational knowledge base and accelerate the training process.

The Next Generation of Search
Traditional Conversational AI
  • Needs 1000’s of Intents
  • Manual effort to train bot
  • Manual effort to update answers post launch
  • Huge effort to enhance and improvise bot
  • Requires a dedicated team of 3-5 employees to maintain bot knowledge base and answers
  • Can answer from structured data
  • Keyword based search
  • No Self-Learning Capabilities
  • No voice-based search
Floatbot QnA - Cognitive Search
  • No need to create and mane intents
  • No manual training of the bot
  • No need to update answers as it finds answers itself
  • No efforts required to enhance and improvise the bot
  • No need to maintain knowledge base and answers
  • Can search from unstructured, diverse datasets
  • Semantic search powered by deep tech NLP
  • Advanced Fuzzy Matching algorithms
  • Supports voice-based search
Pre-integration with Popular Knowledge-bases
Atalassian KMS Salesforce Oracle Zendesk
sementic search
Semantic Search

Instead of searching for keywords, Floatbot QnA performs a semantic search. For example, if you search "What is Cognitive Search?" and then search "How does it work?" Here, Floatbot QnA understands that "it" in the second query is referring to "Cognitive Search" from the first query


Cognitive search leverages Floatbot's advanced NLP (with proven 95%+ accuracy) to enable users to perform a search in natural, human language instead of using a combination of keywords. It enhances user experience

fuzzy matching
Fuzzy Matching

Fuzzy matching finds matches corresponding to queries that are not 100% accurate. It takes care of misspellings or scrambled words. For example, if you search for "intrst rate maximum, " the fuzzy matching algorithm will understand that you're searching for "Maximum interest rate."

Unsupervised Learning
Unsupervised Learning

Floatbot QnA uses advanced unsupervised leading models to self-learn continuously. It helps the user to discover accurate, personalized answers based on search history. Also, Floatbot QnA self-trains itself from unstructured datasets.

Increase CSAT
Scores by 80%
Increase CSAT
Increase Agent
Productivity by 50%
CSAT Improvement
Reduce Operational
Costs by 40%
Reduce Operational
Pre-Integrated with the
Popular Contact Center Solutions
nice in logo
Have Questions? Learn How to Implement Cognitive Search