Natural Language Processing (NLP) Solutions

ZechionAI assists companies in determining areas which areas NLP can be used to improve their the customer experience, operations Knowledge management, customer experience, or decision-making support.

Practical Applications

An organization could be able to manage thousands of support email but there is no effective method of categorizing them. There may be useful internal documentation but not have enterprise search capabilities. The third option is an LLM assistant, but first it needs to know if the information, permissions, and the knowledge infrastructure are in place.

NLP consulting aids in separating attractive ideas from projects that are backed by an actual business case.

Business Benefits

• Better technology-based decisions
• Clearer implementation priorities
• Risk reduction for projects
• More aligned Between AI and business goals
• More realistic planning for investment

Next Step: Begin by conducting the NLP opportunity assessment prior to taking the plunge into a major implementation.

Understand What People and Documents Are Actually Saying

The ability to match keywords is rarely enough. Modern NLP systems evaluate language using intent or context, topics, entities and connections.

Business Applications

NLP can assist in determining whether the customer is asking for an refund, registering an issue with their computer, requesting information about their account, or just requesting information, even when customers have totally different words.

It is also possible to identify companies or individuals, companies dates, locations, policies, references, and other pertinent individuals in business documents.

Business Benefits

• A more accurate interpretation of text
• Better automation decisions
• Improved routing
• More useful search
• Less reliance on strict rule-of-thumbs

This is especially useful in situations where the language spoken by employees, customers or partners is a variety that is difficult to handle manually.

Turn Unstructured Text Into Organized Business Information

Companies often have to spend a lot of time separating emails, documents and forms, tickets and other texts into groups before work can be started.

NLP can help automate a large portion of this initial structure.

Enterprise Applications

Examples include:

• Automatically classifying Support tickets automatically
• Identifying different types of documents
• Extraction of policy numbers from insurance documents
• Recognizing contract clauses
• Information about customers extracted from letters
• Emails to departments that are routed
• Categorizing product feedback

Business Benefits

• There is no need for manual sorting
• Speedier processing of information
• A more than one consistent categorization
• Improved workflow routing
• Easier downstream automation

Next Step: If your employees spend a lot of time reading and separating incoming data, then text classification could be a great automation opportunity.

Make Business Documents Easier to Process

Business information that is important to businesses is typically hidden in PDFs forms, documents, scans contract invoices, claims reports, and other documents.

Document intelligence blends technology to process documents and NLP to discover what documents include.

How It Can Be Used

A document processing workflow can detect incoming documents identify its kind and extract pertinent information, confirm necessary fields, and then forward the document to the appropriate system of business or an employee to review.

Business Benefits

• Reduced manual data entry
• Faster document handling
• More reliable processing
• More information access
• Improvement in workflow efficiency

In the case of documents that have a high impact Human review is a an element of the process instead of forcing total automation.

Search for Meaning, Not Just Keywords

Traditional search usually relies on the exact word that the user has entered.

Semantic search is a distinct method. It seeks to determine the significance of a query and to determine what information is meaningful even when the source document employs different terms.

Example

Instead of looking for:

"employee reimbursement policy"

A worker might be asked:

"How much can I claim for business travel?"

A semantic search system that is well-designed can help identify relevant policies even if the words do not coincide with the text.

Business Benefits

• Faster information discovery
• Improved self-service for employees
• Access to knowledge is improved
• The time spent looking for information is reduced.
• Better experience in the search for business

Semantic searches are particularly beneficial in organizations that have large collections of knowledge and documents that employees have to work through.

Build Conversations Around Real Business Needs

Chatbots are the most effective in situations where they address an employee, customer or operational issue.

ZechionAI can assist in the design of chat applications that are able to understand the user's intention, keep context in mind as well as retrieve information relevant to the conversation and integrate conversations with business workflows.

Business Applications

Business Benefits

• Access to information faster
• Reduction of the amount of repetitive support work
• More regular responses
• Improvements in self-service
• Improved support team efficiency

For complex or sensitive situations, the system may be designed to pass conversations to human personnel.

Connect AI to the Knowledge Your Organization Already Owns

Large language models can be powerful, however general-purpose models don't automatically detect your company's current internal policies, procedures, documents customer information or even proprietary information.

The Retrieval Augmented Generation (RAG) is a way to link to an AI application to authorized sources of information for enterprises.

Why RAG Matters

Instead of relying on the data contained in models, an RAG application can pull relevant information from a variety of sources and utilize the information to come up with an answer.

A well-designed implementation will also take into account:

RAG can assist in reducing non-supported responses, however it doesn't stop hallucinations from occurring or ensure that each answer generated is accurate.

Business Applications

Understand What Customers and Employees Are Saying at Scale

Customer feedback is valuable however, manually reviewing hundreds of reviews or surveys, tickets email, and other conversations is a challenge.

NLP can aid organizations in identifying patterns within vast amounts of text.

Business Applications

Companies can look over customer feedback to determine recurring complaints issues with the product, problems with service and positive customer experiences.

For example, a retail store can analyze reviews to find that consumers consistently praise the product's quality but express confusion at the checkout process.

This knowledge can be used to inform product or operational decision-making.

Business Benefits

• A better understanding of the needs of customers
• Rapider identification of issues that recur
• A more actionable feedback analysis
• Improved customer experience decisions
• Scalable voice-of-customer intelligence

Make Large Amounts of Information Easier to Consume

Employees are often occupied for hours with emails, reports, meetings and customer interactions, case and other documents.

NLP as well as generative AI transform long-winded content into concise, organized outputs.

Practical Examples

An organization for support can provide a summary of a customer's experience prior to contacting an agent.

The management team may receive brief summaries of the operational reports.

A professional or legal service provider could design written summaries of long documents to be reviewed internally.

Business Benefits

• A shorter time spent re-reading data
• Access to the most important points faster
• More consistent documentation
• More efficient flow of information

When it comes to customer-facing, controlled or other high-impact content the human review process and validation is essential.

Make Language Intelligence Work Across Markets

Companies operating across different regions might require processing data in multiple languages, while maintaining the terminology, context, and business context.

Business Applications

Quality of translation depends on the contextual factors, language and terminology, type of document and domain.

In certain industries, management of terminology and human reviews may be required.

Business Benefits

• A wider customer reach
• More information is available
• Faster multilingual processing
• Increased knowledge sharing across markets

Turn Conversations Into Searchable, Usable Information

Meetings, customer calls and interviews, as well as support conversations and audio conversations contain valuable data that is difficult to evaluate if they are recorded.

Speech and NLP technology can transform information into text or well-structured information.

Business Applications

The performance can differ based on accents, background noise the quality of audio, speakers overlap the language used, and domain.

The solution for production must be compared with the company's current audio-related environment.

Build Specialized Models When General Solutions Are Not Enough

Off-the-shelf NLP services can help solve a number of commonly-asked questions. Certain organizations have specific terms, requirements for classification workflows, datasets, or other requirements which require a specific approach.

When Custom Development Makes Sense

Custom-designed development is a possibility for the following reasons:

• Generic models don't perform well enough.
• The organization uses specialized terms
• The classification categories are very specific.
• Proprietary data can provide a significant benefit to training
• The APIs currently in use don't meet the workflow requirements
• Performance must be optimized for a specific area

Customization isn't always the most effective option. It is important to consider the availability of data, the performance requirements maintenance, cost and alternatives.

Apply Large Language Models to Practical Business Problems

LLMs have widened the scope of what companies can do with technology for language But successful enterprise implementations require more than just connecting an application to an API.

Practical Applications

The right model will depend on factors like the requirements for quality and data sensitiveness as well as latency, integration requirements scale, and operational cost.

Fine-tuning may be beneficial in certain situations, but it's not necessary for all enterprise LLM application.

The goal is to create technology that reflects the way an company actually operates, not to force a model that is already in place into an inappropriate workflow.

Adapt NLP to the Language of Your Industry

Language is heavily dependent on its context.

Legal, finance, healthcare services manufacturing, logistics, and healthcare all employ terminology and workflows which general-purpose systems might not fully comprehend.

ZechionAI is able to design NLP solutions based on industry terminology as well as the organization's processes, requirements for data and controls that are applicable.

Connect Language Understanding to Business Processes

NLP provides more value when it triggers an action, not just create an analysis.

Example Workflow

A customer's email incoming could include:

Received - classified – relevant information extracted - priority determined – sent to the team that is most appropriate The CRM records the information and then summarized for the employee.

The workflow may also be accompanied by human approval where judgement or accountability is required.

Business Benefits

Production NLP Requires Continuous Evaluation

The deployment of an NLP system isn't an end to the road for the project.

Languages change. Customer behavior changes. Documents are updated. Business processes evolve. Models and services are modified.

ZechionAI helps organizations set up procedures for monitoring and evaluation that find performance issues and help guide continual improvement.

Why Evaluation Matters

A model that is successful in a developing environment might be different when interacting when interacting with real-world data.

Evaluation must therefore take into consideration the actual needs of the company as well as information, users as well as risk levels and the business needs.

Business Benefits

• Improved production reliability
• Early detection of performance issues
• Controlled model improvement
• Improved visibility of operating costs
• More sustainable AI deployments

In healthcare settings, HIPAA requirements may need to be taken into consideration. Enterprise clients might also be subject to obligations to secure their data related to SOC 2 as well as NIST-based security controls and state privacy obligations or other requirements specific to the industry.

The degree of compliance depends on the particular application, data, environmental as well as contractual obligations and the law applicable to it. Implementation of technology alone will not guarantee compliance for a company.

Build NLP Systems With Security and Accountability in Mind

Language systems can be able to process sensitive customer data employees' communications contracts financial records, healthcare data, or business information.

Governance and security should, therefore, be considered in the architecture, and not later on after the deployment.

Move From NLP Prototype to a Reliable Business Capability

An NLP solution should integrate into the current technology infrastructure.

ZechionAI can assist with moving from prototyping to manufacturing connecting language capabilities to business applications, and creating an approach to manage the process continuously.

Deployment Considerations

Solutions can be designed to meet the requirements of:

Ongoing Optimization

Post-launch support may comprise:

The aim is to develop an effective language solution that will remain effective as the business grows.