Making sense of natural language is hard.
HumanFirst makes it easy.
Everything you need to explore, create and scale AI data,
regardless of technical skillset.
Explore and label your unstructured data using real-time, human-in-the-loop semantic search.
Curate your data into flexible, modular hierarchies that can easily scale to thousands of intents and be re-used across projects, teams and workspaces.
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Accelerate the discovery of topics and intents in your data with built-in unsupervised clustering.
Our human-in-the-loop workflow allows you to configure the clustering parameters (granularity, size of clusters) in real-time, as well as to apply the clustering to specific intents (to find related clusters).
Clustering accelerates labeling
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Identify and move ambiguous training phrases between intents, split intents into more specific sub-intents, and merge conflicting intents together, to guarantee each intent has a clear, laser-focused scope.
Our machine-learning powered workflows let you move hundreds of utterances around with a single click, and preview changes to avoid errors.
Disambiguation is key to optimizing chatbots
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Evaluate the performance metrics of each intent, with unlimited on-demand K-fold split analysis.
Quickly identify problematic intents, and immediately apply our real-time labeling and disambiguation workflows to improve the model's performance.
Track changes to your data that might affect performance of your NLU models with powerful revision and diff capabilities.
Disambiguation is key to optimizing chatbots
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HumanFirst is the complete productivity suite for every use-case that depends on natural language data.
Continuously improving the accuracy and coverage of chatbots, virtual assistants and other conversational AI experience post-deployment requires discovering and training intents from historical or real-time conversational AI data, at scale.
Searching through emails, tickets, live chat and other support channel data using semantics, not keywords.
Tracking and reporting specific customer requests, helping product and operations teams identify opportunities to improve quality and performance of agents and self-serve experiences.
Exploring voice of the customer data and curating, organizing and sharing repositories of labeled verbatims and conversations around any topic or intent. Flagging trends and signals in data. Save your results as intents, re-use them as search filters.
Measuring and improving the performance of models, with powerful intent splitting, merging and disambiguation features powered by real-time ML recommendations.
Transform call center transcripts, chat logs, customer reviews, help center tickets, search queries etc into perfectly categorized and accurate knowledge and AI training data.
Import your raw, unstructured data from live chat, voice calls, product reviews, tickets, help center search logs and any other natural language data source.
Export your high-quality, labeled data from HumanFirst back into your workflows thanks to our robust integrations, APIs and command-line tool.
Share your search results and insights (as labeled data) as quickly as you create them, to support your team with immediate qualitative insights that support decisions and accelerate priorities.
Easily copy/paste or export any subset of your data as CSV.
Using Excel, or building & maintaining tooling to scale NLU is painful, costly and time-consuming.
HumanFirst makes working with natural language data easy, regardless of technical skillset.
Our workflows accelerate the exploration, labeling and management of your data.
No pre-training required.
Import voice transcripts, live chat logs, email, help desk search queries and tickets, chatbot interactions, social media, and any other natural language data.
Multi-lingual out of the box.
From scratch-pad to production data, workspaces allow teams to collaborate around all natural language data, across all use-cases
HumanFirst ingests, indexes and provides real-time processing capabilities across your datasets.
You own the data.
We're GDPR compliant, hosted on Google Cloud infrastructure. If you'd like to deploy to your own cloud, we have a container for that.
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