Pienso
Description
🖼️ Tool Name:
Pienso
🔖 Tool Category:
AI-powered no-code model building & language-data analytics platform — it primarily fits under 44 — Integrations & APIs and 97 — Analytics & Dashboards in your classification list.
✏️ What does this tool offer?
Pienso enables subject-matter experts (not just ML engineers) to build, train, annotate and deploy custom language-AI models — without writing code.
Some key features:
Ingest raw data (structured or unstructured: transcripts, emails, documents, etc.) into the platform.
A “Fingerprinting” workspace where you refine categories, train models, apply your domain knowledge.
Annotation tools: label datasets and apply trained models to new data for insights.
Data-set analysis & visualisation: explore large datasets, try thresholds, and deploy models.
Option for on-premises or cloud deployment; full control of your data & models.
⭐ What does the tool actually deliver based on user experience?
Makes AI model building accessible for non-coders: domain experts can build and fine-tune models themselves.
Helps organisations process large volumes of language/unstructured data (call transcripts, documents) with less manual analysis: e.g., one customer saved millions in costs by using Pienso to analyse call-centre data.
Strong focus on data privacy and customisation: you own the models and data, can deploy in environment you control.
🤖 Does it include automation?
Yes — Pienso automates many steps:
Raw-data ingestion and preparation (for structured/unstructured).
Model training/fingerprinting using non-engineers’ input.
Annotation workflows and applying models to new data for inference.
Deployment as bespoke models (own environment) and integration via APIs.
💰 Pricing Model:
Specific pricing not broadly published; likely enterprise licence model.
Users have to “contact for pricing” in many listings.
🆓 Free Plan Details:
No clear public free plan or easily accessible individual plan found.
💳 Paid Plan Details:
Typically enterprise features, large data volumes, customised deployment.
Some references: “Customers pay a yearly license based on number of AI models deployed”.
🧭 Access Method:
Via web platform:
Demo booking available on the site.
Deployment options include cloud or on-premises.
🔗 Experience Link: