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.
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:
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:
Fully managed solutions
Additional costs may apply for:
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.
Converseon provides a range of training and onboarding support to ensure the successful adoption of its platform:
Converseon has implemented robust data security and privacy measures, particularly in compliance with the General Data Protection Regulation (GDPR). Key security practices include:
These measures ensure that client data—especially sensitive consumer insights—is handled with the highest level of integrity and security.
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:
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.
Converseon’s Privacy Policy and Data Processing Addendum (DPA) outline its stance on data ownership and portability, particularly in compliance with GDPR:
Clients can request a copy of the DPA or contact Converseon’s compliance team for further details.
Converseon offers flexible deployment options that support both scaling up and down based on business requirements:
This scalability ensures that Converseon remains a viable solution for both small teams and large enterprises, adapting to changing strategic goals and operational demands.
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:
