.png)
.png)
2 minutes
Turn incomplete customer data into customer knowledge
Customer data is of paramount importance to maintain a thriving relationship with customers. This data can manifest itself in many forms and is acquired in many ways, whether through voice conversations (phonecalls mostly), meetings notes, or via email.
Incorporating this knowledge into CRM tools obviously allows for better relationship management by understanding customers and their needs more closely. These data points become essential in order to stand out from the competition and create a competitive advantage.
However, the mass of unstructured information today prevails in CRMs (about 80% of a CRM's database is unstructured). In fact, the lack of structure of these data sources (e.g. recordings of telephone conversations) does not make it easy to use the data. If 80% of the data is unstructured, then this means that organizations only make decisions with the remaining 20% that are actionable. They are missing out on a gold mine.
Make the most of your customer data with Natural Language Structuration
Lettria develops solutions for analyzing large amounts of data through the semantic analysis of existing interactions. These knowledge structuring tools can be directly integrated into CRM systems to automatically populate them.
This solution adapts to the context of each company, who can in turn indicate the data they wish to collect on their customers and partners. This is called a customer's "knowledge ontology," in other words, a series of key concepts associated with an individual: important events, essential information and attributes.
Structuring data in software suites makes sense for many industries. Here are some use cases:
- Health: The care path of a patient, especially in a hospital, generates a significant source of unstructured data. This data is vital! It contains health information and influences the practitioner's diagnosis. Discover how Lettria helped the AP-HP to automatically analyze hospitalization reports in order to extract key information about the patient and to store it directly in the patient's computerized file.
- E-commerce: Optimize emailing actions by increasing customer knowledge and adding qualitative elements when creating an audience. Example: Send a promotional email to all customers who have expressed a negative feeling about the price of a product in the last 6 months.
Frequently Asked Questions
Yes. Lettria’s platform including Perseus is API-first, so we support over 50 native connectors and workflow automation tools (like Power Automate, web hooks etc,). We provide the speedy embedding of document intelligence into current compliance, audit, and risk management systems without disrupting existing processes or requiring extensive IT overhaul.
It dramatically reduces time spent on manual document parsing and risk identification by automating ontology building and semantic reasoning across large document sets. It can process an entire RFP answer in a few seconds, highlighting all compliant and non-compliant sections against one or multiple regulations, guidelines, or policies. This helps you quickly identify risks and ensure full compliance without manual review delays.
Lettria focuses on document intelligence for compliance, one of the hardest and most complex untapped challenges in the field. To tackle this, Lettria uses a unique graph-based text-to-graph generation model that is 30% more accurate and runs 400x faster than popular LLMs for parsing complex, multimodal compliance documents. It preserves document layout features like tables and diagrams as well as semantic relationships, enabling precise extraction and understanding of compliance content.
