Data Ingestion: Users begin by uploading unstructured text data—such as emails, contracts, transcripts, or social media posts—into Pienso’s Ingest module. This step is immediate and supports various formats.
Model Training via Fingerprinting: Users refine Pienso’s initial categorization using their domain expertise. This interactive process helps “fingerprint” the model to match specific business language and context.
Annotation and Labeling: Pienso Annotate allows users to label datasets quickly, which are then used to train deep learning models tailored to the organization’s needs.
Analysis and Visualization: Once trained, models are applied to datasets for real-time analysis. Users can explore insights through visual dashboards and adjust thresholds or filters as needed.
Deployment: Models can be deployed on cloud platforms (AWS, Google Cloud) or on-premise, depending on the organization’s infrastructure and compliance requirements.
Timeline: Implementation can vary based on data volume and team size, but most organizations begin generating insights within days to a few weeks, thanks to Pienso’s no-code interface and guided workflows.
Customisation
No-Code Model Training: Pienso allows users to train NLP models without coding, making it easy to tailor models to specific business language, sentiment, or classification needs.
Domain-Specific Fingerprinting: Subject matter experts can refine model categories using their own knowledge, ensuring outputs are aligned with industry-specific terminology.
Flexible Deployment Options: Supports cloud (AWS, Google Cloud) and on-premise setups, allowing businesses to meet security and compliance requirements.
Integration with Leading LLMs: Compatible with OpenAI, Hugging Face, Anthropic, and others, enabling users to select the best foundation model for their use case.
PromptFactory Tool: Helps users craft production-grade prompts for LLMs, enabling deeper customization of model behavior and responses.
Real-Time Updates: Models can be retrained and updated as language evolves, ensuring continued relevance and accuracy.
Use Case Versatility: Applied across industries like finance, government, media, and customer experience for tasks such as sentiment analysis, risk detection, and feedback classification.
Additional Costs
Pricing Model: Pienso uses a pay-as-you-deploy model—users can experiment freely and only pay when deploying models into production.
Setup Fees: No standard setup fee is publicly listed, but enterprise deployments may involve custom onboarding or integration costs depending on scope.
Maintenance: Ongoing maintenance is typically included in enterprise plans, especially for cloud-hosted solutions. On-premise setups may require additional IT support.
Support Charges: Enterprise clients likely receive dedicated support, though specific tiers or charges (e.g., premium support)
Licensing: Pricing is custom and varies based on team size, deployment scale, and integration needs. There’s no free trial currently offered.
Training
No-Code Onboarding: Pienso is designed for non-technical users, so no coding or deep learning expertise is required to get started.
Interactive Learning Interface: Users learn by doing—through tools like Fingerprinting and Annotate—which guide them in training models using their own data.
Guided Setup: Pienso offers assistance in connecting your internal data sources to the platform, whether on-premise or cloud-based.
PromptFactory Tool: Helps users craft production-grade prompts for LLMs, enhancing their ability to customize model behavior without technical skills.
Hybrid Team Support: Business analysts and data scientists can collaborate within Pienso, with analysts driving model creation and scientists assisting with data integration.
Demo and Consultation: Pienso provides demos and personalized consultations to help teams understand the platform and tailor it to their needs.
Security Measures
Self-Contained Platform: Pienso operates entirely within the user’s chosen environment—cloud or on-premise—ensuring no data is sent to third-party APIs.
Data Sovereignty: Users retain full control over their data and models; Pienso does not access or use customer data for training1.
Encryption: All data is encrypted both at rest and in transit, protecting sensitive information from unauthorized access.
SOC 2 Attestation: Pienso has achieved SOC 2 compliance, demonstrating its commitment to high standards of data security and system integrity.
Trusted by Governments and Financial Institutions: The platform is used by organizations with strict security requirements, reinforcing its credibility
Updates
Regular Updates: Pienso evolves its platform continuously to improve performance, usability, and compatibility with emerging LLMs and cloud technologies.
User-Controlled Model Evolution: Users can retrain and refine models as language and business needs change, ensuring ongoing relevance.
Safe Deployment: Updates are managed within the user’s secure environment, avoiding disruptions and maintaining compliance with internal IT policies.
PromptFactory Enhancements: New features like PromptFactory are rolled out to help users stay ahead in prompt engineering and model customization.
Data Ownership and Portability
Full Data Ownership: Clients retain full ownership of all data they upload, generate, or process within Pienso. The platform does not claim rights over user data.
No Data Resale or Aggregation: Pienso does not resell, aggregate, or repurpose client data for third-party use. All data usage is confined to the client’s operational scope.
Portability Assurance: Upon contract termination, clients can request the return of all their data. Pienso ensures that no backup copies are retained unless explicitly agreed upon.
Encrypted Data Transfers: Data portability is supported through secure, encrypted channels to maintain integrity during migration.
Custom Destruction Protocols: If data return is infeasible, Pienso offers verified destruction protocols to ensure complete removal from its systems.
Scaling Up / Down
Flexible Licensing: Pienso’s licensing model allows organizations to scale usage based on team size, data volume, or project scope.
Pay-as-You-Deploy: Users can experiment freely and only incur costs when deploying models, making it easy to scale down without penalty.
Cloud and On-Premise Options: Organizations can shift between cloud-based and on-premise deployments depending on evolving infrastructure needs.
Modular Access: Features and integrations can be added or removed as needed, supporting agile growth or contraction.
The terms & conditions for contract renewal and cancellation
Custom Contracts: Pienso offers tailored agreements based on deployment type, team size, and industry requirements.
Renewal Flexibility: Contracts may be renewed annually or per project basis, depending on the client’s preference.
Cancellation Protocols: Clients can terminate contracts with notice, typically requiring data return or destruction as part of the exit process
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No Lock-In Clauses: Pienso emphasizes user control and avoids vendor lock-in, supporting smooth transitions if clients choose to exit.
Support During Transition: Upon cancellation, Pienso provides assistance with data migration or secure deletion to ensure compliance and continuity.
Compliance
SOC 2 Attestation: Pienso meets SOC 2 standards for data security, availability, and confidentiality.
GDPR Compliance: The platform aligns with GDPR requirements for data privacy, user consent, and processing transparency.
CCPA Alignment: Pienso supports California Consumer Privacy Act (CCPA) principles, including data access and deletion rights.
Enterprise-Grade Security: Used by government and financial institutions, Pienso adheres to strict internal and external compliance protocols.
