Customize Generative AI,
no code required!
Texti is your gateway to the power of foundational AI models.
With its no-code-first perspective, it ensures that everyone, irrespective of their technical expertise, can harness the full potential of AI.
What is Texti.ai ?
Texti.ai is a no-code platform that allows for no-code customization of foundational AI models through fine-tuning and in-context learning.
Above all, it is agnostic to specific AI models, offering broad compatibility and flexibility.
Fine-Tuning
Fine-tuning is a powerful technique used to improve the accuracy of AI models. By training a pre-existing model on a smaller, specific dataset for a new task, it enhances its accuracy for that particular task. Read more.
In-Context Learning
In-Context Learning with Retrieval Augmented Generation (RAG) enhances large language models (LLMs) by integrating external information. AI Co-Pilots are built using this powerful technique. Read more.
Texti’s features at glance
All Models, One Place
Texti serves as a unified platform for customizing both proprietary and open-source foundational AI models. It is agnostic to specific AI models, offering broad compatibility and flexibility.
Collaborative Labelling
Texti streamlines collaborative labelling.
It employs majority voting for class selection, balances datasets for text-classification tasks, and allows shared editing of labeled instances for text-generation tasks.
AI & Data Governance
Ensuring all stakeholders have transparency into the data used for customizing AI models is pivotal. This transparency not only aids in identifying and eliminating potential biases but also establishes robust governance in AI and data management.
Explainability & Evaluation
Evaluating performance of different foundational AI models on identical tasks is crucial for a cost-effective selection of the most accurate model, one that's best adapted to the specific task and data.
Texti facilitates this essential evaluation, ensuring optimal outcomes
Easy-to-Use Data Connectors
With Texti, users have the flexibility to bring their data seamlessly. For fine-tuning, they can utilize SQL, Google Sheets, or CSV.
And for in-context learning, unstructured data in PDF or .txt formats is readily supported
Fine-Tuning
Typical workflow
No collaboration, constant coding, limited data transparency, and slow evaluations.
No Code Fine-tuning with Texti
Zero lines of code required, collaborative approach, and easy evaluation.(or select hyperparameters)
In-Context Learning
Typical workflow
Data engineering required and lack of collaboration.
No Code In-Context Learning with Texti.ai
Embedding selection, automated workflows, and evaluation support.(or select Hyperparameters)
ready-to-use AI Co-Pilot
Become an AI expert without writing a single line of code – ride the new wave with Texti!
Why Customize foundational AI Models?
Tailored
Solutions
AI-Driven
Automations
Enhanced
Performance
Cost
Efficiency
AI Governance &
Bias Mitigations
Data Privacy &
Compliance
Industry Examples
Human Resources
Engineering
Healthcare
Legal
Investing & Finance
FAQ’s
