Pienso
Empower data analysis without coding; intuitive, customizable AI tool.. [Contact for Pricing]
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What is Pienso?
Pienso is an interactive AI platform that enables anyone with a text dataset and a question to create, train, and deploy custom large language models without writing a single line of code. The platform uses machine learning to explore language data through an interactive and responsive learning interface that imprints user expertise at AI scale. It is built for serious business applications and is designed for subject matter experts who want to explore every corner of their data.
The platform offers four core modules: Ingest accepts raw and unstructured data from emails, contracts, phone logs, and libraries, analyzing text instantaneously and categorizing it into topics; Train and Fingerprint puts users 'in the loop' with a unique Fingerprinting Workspace to refine categorization and train models until fingerprinted to satisfaction; Annotate applies trained models to quickly label datasets for deep learning analysis; and Data Set Analysis enables fine-tuning and discovery through visualizations and threshold experimentation. Pienso also introduces PromptFactory to help users become fluent in constructing production-caliber prompts without code.
Pienso is designed for non-technical users, data scientists, analysts, researchers, marketers, and customer support teams who have access to large amounts of text data but lack resources to structure and analyze it. Key use cases include content moderation, customer insights (sentiment analysis, agent performance evaluation, churn prediction), document intelligence (classification, risk detection), and cybersecurity (retraining models as criminal strategies evolve). Sky, the UK's largest pay-TV broadcaster, uses Pienso to analyze over 500,000 customer calls weekly.
The platform emphasizes data privacy and model ownership—your data stays private since Pienso runs in your environment (cloud or on-premises), and you own your models with complete control over their integrity. Unlike closed-model providers like GPT-4 that can suddenly change parameters, Pienso users have full transparency and can change LLMs as needed. Deployment is quick and cost-effective with pay-only-upon-deployment pricing.
Pienso pricing
Pricing model: Freemium
Pienso uses a yearly license pricing model based on the number of AI models deployed—the greater the number of models, the higher the licensing cost. Users pay only when they deploy models, not during training. The platform is installed in the customer's preferred environment (on-premises or cloud) with no additional resources needed to run it. No free tier is mentioned on the website; interested users must book a demo to get pricing details. Companies pay based on how many models they deploy, and the platform can operate without APIs or third-party services keeping data within a secure environment.
Pienso pros
- No-code interface for creating and fine-tuning ML models
- No technical expertise or Python programming required
- Interactive Fingerprinting Workspace puts users in the loop
- Real-time feedback while tagging improves label clarity
- Fast model training with speedy throughput
- Live predicted class updates during tagging process
- Works with both structured and unstructured data
- Custom models trained on your own company data
- Complete ownership of AI models with full control
- Data stays private—runs in your environment
- Deploy in cloud or on-premises under enterprise security
- Pay only for models when deployed, not during training
- Can change LLMs as needed for different use cases
- Low-latency deployment through trusted partners like Gcore
- Visualizations for dataset analysis and insight discovery
- PromptFactory for production-caliber prompt construction
- Error analysis and precision/recall graphs for model inspection
- Built-in API for pulling results and batch file downloads
- Models improve and evolve as you refine them
- Handles vast amounts of text data in real time
Pienso cons
- Limited export options for annotated datasets
- Basic REST API knowledge needed for data source connection
- Limited tutorial support for new users
- Requires subject matter expertise in your data
- Hybrid team needed—analysts plus data scientists
- No free tier mentioned—requires booking a demo
- Yearly license pricing based on number of models deployed
- Cloud regions currently limited to North America and Europe
- On-premises installation requires customer environment setup
- Multi-tenancy not available—each installation is isolated
Frequently asked questions about Pienso
Do I need coding skills to use Pienso?
No, you don't need to know how to code. You simply need to be an expert in your own data with a nuanced understanding of it. Pienso's motto is that those who best understand their data should be the ones creating the models. No technical expertise such as knowledge of deep learning or Python programming is needed to create and fine-tune models.
What technical expertise is required?
No technical expertise like deep learning or Python programming is needed to create and fine-tune models. Connecting the Pienso platform to your data sources requires only a basic understanding of REST API handling. Ideally, individuals creating and fine-tuning models should have a nuanced understanding of your data sources. Most customers consist of a hybrid team: business analysts who create models and data scientists who assist with connecting Pienso to internal data sources.
What can I use Pienso for?
With Pienso, you can create your own large language model to analyze vast amounts of text data in real time, including customer conversations, documents, research articles, news articles, or any other text content. Customers use it for real-time monitoring of customer conversations, analyzing customer success, tracking narratives and trends, personalizing fintech information, automating understanding of insurance documents, content moderation, customer insights (sentiment, agent performance, churn prediction), and document intelligence (classification, risk detection).
What does deploying a model mean?
Once you have trained or fine-tuned a model using historical data from your enterprise, deploying it means putting it to use to analyze new data. You can deploy your fine-tuned LLM in your own environment under enterprise security, or accelerate deployment on cloud through trusted low-latency partners like Gcore for ideal security and speed combination.
How do I get my data into Pienso?
Pienso's Ingest module allows you to import data into the platform from your data sources. You can add text by dragging CSV, JSON, or live stream files into the dashboard. Additionally, Pienso can collaborate with you to connect your data sources to your Pienso platform installation. The platform accepts raw and unstructured data from emails, contracts, phone logs, and libraries.
Is my data secure with Pienso?
Yes. Since Pienso is installed in the environment of your choice (on-premises or cloud), only you have access to your data. Pienso does not see or access your data or your models. All data is stored securely with encryption at rest and encryption in transit. Pienso does not use your data in any way and your installation is solely for you with no multi-tenancy.
Does Pienso use my data to train their models?
No, Pienso does not use your data in any way and they do not have any access to it. Your installation of Pienso is solely for you and is not shared with any other customer (no multi-tenancy). While some closed model providers use customer data to train their models, Pienso's in-cloud, on-premise operation means your data remains entirely yours.
Who is Pienso built for?
Pienso is designed for anyone with a dataset and a question, including non-technical users, data scientists, analysts, researchers, marketers, and customer support teams. It's built for subject experts who have access to large amounts of data for AI training but lack resources to structure and analyze it. The platform works whether you're a non-technical type, data scientist, or analyst, and whether your data is structured or raw.
What makes Pienso different from closed-source LLMs?
With Pienso, you have complete control over your models—no changes that you haven't made yourself. Closed-model providers like GPT-4 can suddenly change parameters, making them unreliable. While some closed-source LLMs allow limited fine-tuning, they're nothing like the customization possible when you can see and change every perimeter. You can fine-tune your LLM and pay only when you deploy, and you can change LLMs as needed.
How do I get started with Pienso?
To get started, you can book a demo through the website. Create an account at pienso.com and choose a project template. Add text by dragging CSV, JSON, or live stream files into the dashboard, highlight and tag samples to teach the system what matters, then click 'Train' to let the engine build a model from the labelled material. If you want to connect Pienso to your data sources, reach out to their team and they'll get in touch promptly to collaborate on the connection.