The implementation of Converseon software typically follows a structured, step-by-step process designed to ensure high accuracy, relevance, and alignment with business goals. The timeline can vary depending on the complexity of the use case, but many organizations begin seeing results within a few weeks to a couple of months.
Here’s a typical implementation process:
Define Use Case The process begins by identifying the specific business challenge or insight need—such as brand reputation tracking, customer experience analysis, or ESG performance measurement.
Data Assessment Converseon evaluates whether sufficient unstructured data (e.g., social media, reviews, call transcripts) is available and relevant to the use case.
Model Selection or Customization Users can choose from hundreds of prebuilt LLM-based models or opt to build custom models tailored to their brand, industry, or domain.
Coding Guidelines and Data Labeling For custom models, Converseon helps define coding guidelines and label conversation data to train the model effectively.
Model Training and Validation The platform uses automated validation scoring and confusion matrix analysis to assess model performance. Errors are analyzed and corrected to improve precision and recall.
Deployment Models are deployed via the Conversus™ no-code platform or through API integrations with third-party tools like social listening, BI, and CX platforms.
Performance Monitoring Post-deployment, Converseon provides dashboards and tools to monitor model accuracy, relevance, and business impact.
Ongoing Optimization Models can be continuously refined based on new data, feedback, and evolving business needs.
Depending on whether prebuilt or custom models are used, implementation can be as fast as a few days for prebuilt solutions or several weeks for fully customized deployments.
Customisation
Converseon is highly customizable and designed to adapt to a wide range of business needs across industries. Here are key data points that demonstrate its flexibility:
Custom Model Development Converseon allows users to build models from scratch or modify existing ones to align with specific brand definitions, industry language, and use cases. This includes sentiment analysis, voice segmentation, consumer attitude modeling, and more.
Industry-Specific Prebuilt Models The platform offers a large library of prebuilt models tailored to industries such as retail, finance, healthcare, and technology. These models are fine-tuned for domain specificity and can be further customized.
Flexible Data Inputs and Outputs Converseon supports a wide range of data sources (social media, reviews, surveys, transcripts) and integrates with various platforms via REST APIs, making it adaptable to existing tech stacks.
Custom Dashboards and Reporting Through its PRISM™ system, Converseon offers customizable dashboards that simulate strategic decisions, forecast outcomes, and tie insights directly to KPIs like sales, reputation, and customer satisfaction.
Voice Segmentation and Content Type Filtering The platform can be configured to distinguish between user-generated content, promotional material, and news, helping businesses focus on the most relevant data.
Consumer Attitude Analysis Converseon’s models can detect up to 15 nuanced consumer attitudes, such as “Aggrieved,” “Grateful,” or “Inquiring,” offering deep customization for customer experience and brand perception analysis.
Political Landscape and Brand Safety For brands operating in sensitive environments, Converseon offers models that identify politically charged conversations and assess their impact on brand safety.
Additional Costs
Converseon’s pricing is primarily subscription-based, with packages starting at $36,000 annually for access to its Conversus™ NLP platform. While specific setup fees and maintenance costs are not publicly itemized, the platform offers flexible options, including:
Prebuilt model subscriptions
Custom model development
Ad hoc insights
Fully managed solutions
Additional costs may apply for:
Custom model training and validation
API integrations
Dedicated support or consulting services.
Organizations are encouraged to book a demo or consultation to receive a tailored quote based on their data volume, use case complexity, and integration needs.
Training
Converseon provides a range of training and onboarding support to ensure the successful adoption of its platform:
No-code interface: The Conversus™ platform is designed for non-technical users, allowing easy model building, validation, and deployment without coding.
Automated validation scoring: Helps users understand model performance and minimize bias.
Prebuilt model library: Offers immediate access to hundreds of industry-specific models, reducing the need for extensive training.
Custom onboarding: For enterprise clients, Converseon offers tailored onboarding sessions, including guidance on model customization, data integration, and performance monitoring.
Resource Center: Includes webinars, documentation, and case studies to help users stay informed and upskill.
Security Measures
Converseon has implemented robust data security and privacy measures, particularly in compliance with the General Data Protection Regulation (GDPR). Key security practices include:
Chief Security Officer oversight: Ensures high standards across all services.
Technical protections: Includes encryption, secure data storage, and frequent system testing.
Employee training: All personnel with access to personal data are subject to confidentiality obligations.
Third-party compliance: No third party processes personal data unless it meets GDPR standards.
Breach notification: In the event of a system breach, Converseon commits to notifying affected clients within 72 hours.
Data retention policies: Personal data is retained only as long as necessary, in accordance with published privacy policies.
These measures ensure that client data—especially sensitive consumer insights—is handled with the highest level of integrity and security.
Updates
Converseon does not specify a fixed update schedule (e.g., monthly or quarterly), but its platform is described as continuously evolving, with frequent enhancements to its LLM-powered NLP models, dashboard features, and governance tools. Updates are managed through:
Automated model validation and scoring systems
Human-in-the-loop governance
Performance observability dashboards
These mechanisms allow Converseon to refine models and platform features dynamically, ensuring high accuracy and relevance. Clients benefit from prebuilt models that are regularly fine-tuned and custom models that can be updated based on new data or changing business needs.
Data Ownership and Portability
Converseon’s Privacy Policy and Data Processing Addendum (DPA) outline its stance on data ownership and portability, particularly in compliance with GDPR:
Data Ownership: Customers retain ownership of their data. Converseon acts as a data processor, using customer-provided or publicly available data solely for the performance of its services.
Portability: Converseon supports data portability by allowing clients to export insights and processed data. This is especially relevant for organizations integrating Converseon with BI, CX, or social listening platforms via API.
Retention Policy: Personal data is retained only as long as necessary, and Converseon commits to deleting or anonymizing data after service termination, in accordance with GDPR.
Third-Party Access: No third party processes customer data unless it meets GDPR compliance standards.
Clients can request a copy of the DPA or contact Converseon’s compliance team for further details.
Scaling Up / Down
Converseon offers flexible deployment options that support both scaling up and down based on business requirements:
Modular Platform Access: Clients can start with prebuilt models and expand to custom solutions, predictive dashboards, or fully managed services.
Subscription Packages: Pricing and access are tiered, allowing organizations to adjust their subscription level as data volume or use case complexity changes.
API Integration: The platform is designed to be data source-agnostic and integrates easily with existing systems, making it scalable across departments or regions.
Model Customization: As needs evolve, clients can fine-tune existing models or build new ones to address emerging challenges or opportunities.
Support for Multiple Use Cases: From sentiment analysis to ESG tracking, Converseon’s platform can be expanded to cover new domains without requiring a complete overhaul.
This scalability ensures that Converseon remains a viable solution for both small teams and large enterprises, adapting to changing strategic goals and operational demands.
Compliance
Converseon is fully compliant with the General Data Protection Regulation (GDPR), which governs the processing of personal data for EU residents. Key compliance measures include:
Data Processor Role: Converseon acts as a data processor, using personal data only for service delivery and in accordance with applicable laws.
Security Oversight: The company maintains a Chief Security Officer and deploys industry-standard technical protections, including encryption, secure storage, and regular system testing.
Employee Confidentiality: All personnel with access to personal data are subject to strict confidentiality obligations.
Third-Party Compliance: No third party processes data unless it meets GDPR requirements.
Breach Notification: In the event of a system breach, Converseon commits to notifying clients within 72 hours.
Data Retention and Portability: Personal data is retained only as long as necessary and can be exported or deleted upon request.
