Bitext Automates Text Data Services for Multilingual GenAI

  • Automation of Data Labelling and Annotation (DAL) tasks
  • Generation of Synthetic Text with proprietary NLG tech
  • Verticalization of LLMs (GPT, Mistral…) in 20 domains (CS, Banking…)
  • Training and Evaluation of LLMs (GPT, Mistral…) for Conversational AI
TravelGPT demo for cellular device

Working with 3 of the Top 5 Largest Companies in NASDAQ

GenAI Data & Models

At Bitext we generate Synthetic Data to verticalize Language Models for Enterprise GenAI, because we believe that Vertical GenAI is critical for success at Enterprise Use Cases

 

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  • DEMOS. Check how these Models work in our Banking Demo. Compare answers from 3 models:
    • ChatGPT-3.5 model: base model that provides general answers
    • Pre-trained Banking: finetuning ChatGPT-3.5 model for the Banking vertical, using Bitext’s generic Retail Banking synthetic dataset
    • Customized Banking: finetuning Pre-trained Banking model for a specific client, using client-specific data, augmented with our synthetic text technology

Currently, we are partners with Databricks and Amazon AWS, providing services that range from data annotation and labelling to verticalized GenAI models. Additionally, we publish our datasets and models publicly on Hugging Face.

NLG Technology to Generate Hybrid Datasets for LLM Fine-tuning

NLG Technology to Generate Hybrid Datasets for LLM Fine-tuning

Our datasets are hybrid datasets because they combine the scale and volume of synthetic text generation with the quality of expert curation. These datasets are tagged with linguistic properties that motivate variation: colloquial/formal language, intentional spelling errors, different syntactic structures, etc.

The datasets are designed to fine-tune Large Language Models (LLMs) for conversational applications and, in particular, for customer support. Our datasets use a hybrid methodology that merges synthetic techniques and linguistic supervision to solve problems that are typical of text produced with generative AI like hallucination, bias, and PII.

Deploying Successful GenAI-based Chatbots with less Data and more Peace of Mind.

Customizing Large Language Models in 2 steps via fine-tuning is a very efficient way to reduce data needs, as well as training and evaluation efforts, when building customized Conversational Assistants. Bitext provides these Pre-Built Datasets and Models in 20 verticals.

Any Solutions to the Endless Data Needs of GenAI?

Discover the advantages of using symbolic approaches over traditional data generation techniques in GenAI. Learn how 100% reliable, bias-free, and PII-free data can be achieved through rule-based generation, ensuring semantic integrity and accuracy. Explore the unique benefits of this method for generating variations from seed sentences with predictable outcomes.

From General-Purpose LLMs to Verticalized Enterprise Models

In the blog “General Purpose Models vs. Verticalized Enterprise GenAI,” the focus is on the advantages of verticalizing AI models for specific enterprise domains. Verticalized models can disambiguate context-specific terms and speak in industry-specific tones. There are two approaches: building models from scratch, which is costly, or fine-tuning general-purpose models with domain-specific data. Bitext proposes a faster two-step method: first, verticalize the model, then customize it with enterprise data. This approach saves time, resources, and avoids common AI issues like hallucinations and bias.

Case Study: Finequities & Bitext Copilot – Redefining the New User Journey in Social Finance

Bitext introduced the Copilot, a natural language interface that replaces static forms with a conversational, proactive, and highly personalized user experience. This change not only simplified the onboarding process but also made it more interactive and capable of resolving queries in real time, offering significant advantages over traditional methods.

Abstract minimalist design visualizing Automating Online Sales with GenAI Copilots by Bitext.

Automating Online Sales with Proactive Copilots

Automating Online Sales with a New Breed of Copilots. The next generation of GenAI Copilots moves from passively answering customer questions to actively executing online sales. These new Copilots are proactive, they can start and drive an interaction with a potential customer; and context-aware, they know the different steps in the sales process, where they are in the process and how to move to the next step.

Taming the GPT Beast for Customer Service

GPT and other generative models tend to provide disparate answers for the same question. Having control is called Fine-tuning.

Can You Use GPT for CX Purposes? Yes, You Can

ChatGPT has major flaws that prevent it from becoming a useful tool in industries like Customer Experience

Worldwide Language Coverage

Worldwide Language Coverage

Need More Info?

At Bitext, we focus on linguistic-based language automation to deliver innovative customer experiences. If you want to test our solutions or learn more, we recommend you schedule a personalized demo from one of our experts.

Request a Demo

MADRID, SPAIN

Camino de las Huertas, 20, 28223 Pozuelo
Madrid, Spain

SAN FRANCISCO, USA

541 Jefferson Ave Ste 100, Redwood City
CA 94063, USA