Most veterinarian practices are small 1 or 2 person operations. Diagnosing, mixing, and administering scrips to sick or injured animals is a challenge in that the animal often must be held by the veterinarian to avoid further pain or discomfort for the patient. Determining correct pharma dosing requires hands-on interaction with a computer which in turn requires restraining the patient, sterilizing hands, entering data, mixing the scrip, and then re-engaging with the patient to administer the pharma. This entire process induces risk to both the patient and the doctor.

Using Soffos' natural language processing modules combined with IoT devices, veterinarians can conduct an entirely hands-free process. This will allow them to hold and comfort the patient while using voice commands to control the operating theatre, request or provide vitals and other patient information including prompts if any information is missing or appears to be inaccurate, verification of pharmaceutical stock and recommendation of alternatives if necessary, and create the required scrip to administer to the animal.

The benefit of this type of NLP includes reduced risk of errors, reduced trauma for the patient, and better control of the operating theatre during patient interactions without the need to add additional personnel, thus maintaining cost control, especially in areas where resources and staff are limited or at a premium.

According to studies, the majority of care professionals experience workplace burnout, which leads to poor patient care. Patients today require undivided attention from their healthcare providers, which leaves doctors feeling overwhelmed and burned out as they provide personalized services while also managing burdensome documentation.

''Medical AMA'' The use of a medical conversational AI agent can assist patients in understanding their symptoms and learning more about their conditions without having to interact with their physician.

Patients Interacting with an intelligent chatbot will help relieve doctors' workload, improve patients' understanding and experience, and provide medical staff with important information. These lead to boosted productivity and reducing the number of resources invested.

Speech recognition (SR) software integrated into electronic health records allows users to create notes to document patient care. While easy to use and efficient, SR is prone to errors, including spelling errors and “real-word” errors, where a correctly spelled word is incorrect in the context of the note. Spell check functionality catches spelling errors, but real-word errors are more difficult to automatically detect and correct. As such, clinicians must proofread and edit SR-generated notes, a step that may be skipped due to time constraints. Errors that are missed become part of the permanent medical record, making those documents inaccurate and potentially impacting future patient care and safety.

Utilizing natural language processing (NLP) improves accuracy of SR notes by automatically detecting and identifying potential errors.

Clinicians can save more time skipping the step of proofreading, automatically detecting errors in electronic patient notes created with speech recognition, with the potential of improving the accuracy, completeness, legibility, and accessibility of medical documents. This leads to enhanced patient safety and health care delivery.

Supply Chain operations involve everything from managing raw materials and supply, to responding to customer orders and managing personnel and transportation and delivery logistics. It is a vast web of information, typically involving numerous applications and software. Finding information on any one of these components can be very complex, especially if it is outside day-to-day responsibilities.

A conversational AI system can connect with data from all kinds of applications and systems, making it easy to ask questions on any aspect of operations. For example, the system can connect with fleet management software to answer questions about driver locations. It can connect with HR data to provide info on personnel who are available, and of course it can tap into knowledge management software to answer questions on anything from QA specs to raw materials' availability.

Information throughout the organization can be easily accessible for answering questions that are critical for customers, for employees, for suppliers and for distributors. This smoother more efficient experience means faster resolutions of issues, decreasing unnecessary costs for the company.

When customers make orders, there are a multitude of points along the journey they might need support, and where the process can be made more seamless. When placing the order there may be questions about how to fill out certain fields. Simply seeing a long form to fill out could be enough to abandon the purchase. Then they might want to update their order, or track it. And there are all kinds of frequently asked questions that come up, but nobody likes sifting through a long page of FAQs to find an answer they need.

A conversational AI agent can guide a customer through the ordering process, just as a human agent would. It can ask for all needed details in a smooth and non-overwhelming way, and make updates and edits to the order if needed. It can also provide tracking details and answer questions that the customer might have.

The customer has a smoother and more supported experience, without placing unnecessary burden on human agents already busy with other more complex inquiries, and without needing to expand the team.

Logistics service provider companies depend on third-party logistics, including common carriers, subcontractor staff, charter airlines, and other third-party vendors to operate core functions of their business. This puts an increased burden on the logistics accounting team to process millions of invoices annually from thousands of vendors, partners, or providers.

The combination of a knowledge management system where invoices, payments and other forms can be stored and converted into knowledge, with a conversational AI system can access information such as billing amounts, account information, dates, addresses, and parties involved from the sea of unstructured invoices and forms received by the company.

Less time is needed by humans to search and query this information, saving costs and resources.

Customers purchasing both in store and online often have questions, issues or concerns that come up before and after purchases. Large teams of customer support agents are costly and challenging to manage. Many companies simply do not have the resources to handle the volume of questions and requests they receive.

Using Soffos' NLP modules, smart conversational AI agents can respond to customer questions by pulling from information in the company's FAQ and knowledge base. These agents do not require decision trees or complicated set up, they are simply able to use artificial intelligence to infer answers. More complex inquiries can be routed to a smaller team of human agents, and analysis of recordings from these conversations can be used to grow the capabilities of the AI agents.

Customers receive answers right away, increasing satisfaction, while companies are able to keep their customer support team smaller, bringing down costs.

As the general population becomes more and more used to the power and efficiency of search engines like Google, their expectations are also rising for any kind of search experience that they have, including for retails sites. If they type a search for a certain kind of item and do not get relevant results, it's an extremely frustrating experience, and one that could cause them to abandon the site altogether.

Using Soffos' natural language search modules, a client can search for a certain category of items, and get relevant results, even if the search does not include item keywords. For example, a search for men's summer shoes could pull up flip flops and sandals, or a search for certain mechanical parts can be made based on the function of the part and not on the actual part number.

Customers have a smoother and more pleasant experience and by finding the items they are looking for, conversion and site revenue increases.

In a typical grocery or other retail shopping experience, customers are navigating through hundreds or thousands of products, searching for multiple items, with uncertainties about item details, locations and about their shopping choices. The whole experience can be overwhelming, and it's one reason why many customers moved away from in-store to online shopping.

Using Soffos NLP modules, customers can ask questions about specific items they are looking for and get the location of items. Products can also be scanned so that customers can ask detailed questions about cost, ingredients, materials and for suggestions about similar items. The app can also make suggestions and flag items as the customer moves through the store.

The customer's experience is greatly improved, as they are spending less time and feeling less frustration as they search for items, and try to make decisions about what item to buy.

Financial firms are often dealing with sensitive and private information, with limitations on who is authorized to view content for the sake of privacy protection. This can create bottlenecks, as solutions to speed up the review or processing of documents become limited by who is allowed to access them.

Using Soffos' named entity recognition module, sensitive information such as company names, individual names, locations and certain numbers can be automatically redacted. This removes the sensitive information, allowing other parts of the documents to be more quickly processed or accessed by other people.

Automatic redaction can greatly speed up processes and save costs versus manual review of documents by authorized persons.

Financial investment firms all have their own "secret sauce" for analyzing market and company information to make critical investment decisions. In all cases it involves sifting through high volumes of company, media, social media and other market data, much of it unstructured. Sorting through this information manually is not scalable. While financial analysis software exists, it provides a one size fits all solution, and often is limited and not up to date with the latest AI advancements.

Soffos' smart platform technology allows companies to create their own analysis tools, using the latest and greatest AI available on the market that will be compatible with all of their internal systems and proprietary technologies. Advances in key AI functions like Named Entity Recognition, summarization, and topic modeling will ensure analysis is at optimal levels.

Companies can be sure they are getting the most advanced R&D developments for their analysis tools, and these can be customized to fit their exact needs, optimizing cost and efficiency.

As part of investment due diligence, financial firms often review earnings calls of target companies to uncover important trends over time. There may be years or even decades of records, all of which can provide unique and significant insights, but which are difficult for a human to sort through and to recognize important patterns.

Using Soffos' smart NLP technology, key topics covered during the earnings calls can be identified and tracked over time, and relationships between topics can also be flagged. Sentiment can also be identified and connected to various topics, using analysis of the language used, as well as voice tone during calls. Raw unstructured files are converted into valuable knowledge and insights.

By using advanced technology, time spent reviewing documents is reduced, and patterns that would be missed by human review are detected, leading to better insights and decisions.

Financial companies are under many strict compliance and due diligence requirements. Fulfilling these requirements often involves sifting through high volumes of documents related to individuals and companies under inspection. This process is not only time consuming, but prone to human error, as humans will naturally tend to tune out and lose focus when reviewing high volumes of tedious material.

Soffos' smart technology can be used to build features that tag named entities within documents such as individuals, companies, codes of law, and date and time references. These can then be easily searched and important information can be discovered.

Important documents are found and discovered more quickly, without the risk of human lapses in attention missing important details

Finance products often involve complex regulations, disclosures, and terms that not only are extremely difficult for a sales team to learn about and know when to reference, but are also changing at a pace that can be impossible to keep up with. Conversations often have to be revisited, and important information provided as follow on discussions, providing a sub-optimal customer experience and impacting trust and the ability to close deals.

Using Soffos' smart platform technology, a live finance product sales support system can be created and customized. During calls with prospects, questions or comments made during the discussion will trigger live product knowledge suggestions, pulling up information on relevant regulations, disclosures, costing or terms. Salespeople can then review this product knowledge on the spot if they are in need of it, and use it to further guide the discussion with the prospect.

When salespeople can pull up information that they need, they can more confidently guide the prospect to the solution that is right for them. This in turn will increase the close ratio, increasing sales revenue.

Recruitment processes are lengthy, involve tedious screening tasks and can become repetitive. Recruiters need to review hundreds, sometimes thousands of resumes for a single job posting. They then typically pre-screen or pre-interview a larger pool of candidates before setting up additional interviews with other team members. It is no surprise that hiring managers can spend hours filtering at the top of the funnel.

‍NLP algorithms can select and rank candidates based on their abilities and filter them for HR and other departments automatically based on the applicant’s resume and motivation/cover letter. A conversational agent can also gather additional initial information from a larger pool of candidates, and make sure that any specific items not covered by the resume or cover letter are addressed.

Hours saved from having to pre-sift through resumes and candidates, reduce time-to-hire and improves the candidate experience, filter for skills, professional backgrounds, and experiences expressed in a CV or professional profile, rank and classify candidate profiles, Identify personal traits, identify gaps in records, remove subconscious bias, increase diversity in candidates.

HR departments spend most of their time on “transactional” tasks, like employee communications, onboarding, managing payroll– all activities that could be either fully or partially automated to free up HR’s time for the more strategic initiatives. In fact, HR professionals want to spend more time on professional development, training employees, and managing company culture instead. The main challenge faced by HR departments is how to respond quickly and efficiently to all employee requests for information. Access to the right information at the right time is essential.

‍An HR conversational AI agent helps employees quickly find the information they need on the organization of the company, its operating rules, internal procedures etc.

This HR conversational AI agent is perfectly capable of answering questions, helping employees and directing them to HR for the most complex issues. It performs these tasks via understanding text or speech (e.g. using natural language processing).

‍Saves time, and effort, improves the employee experience, helps employees get quick answers, reduces the possibility of human error, and keeps HR processes going even if HR employees are on leave or sick. They’re cost-effective since they’re always “on” but will only need to be set up once, companies also save costs: employees won’t waste paid hours on tasks the Conversational AI agent can handle on its own

There are many tedious, routine and time-consuming administrative tasks that need to be carried out that don’t allow lawyers to focus on billable tasks (tasks that need their attention the most). Law offices get inundated with enquiries. There may be enquiries received over the weekend, during lunch, or after working hours. Unanswered enquiries may result in missed opportunities.

‍Soffos' smart platform can be used to create an advanced conversational agent as the initial contact point of your firm’s customer service.  

A Conversational AI agent can automatically answer routine client questions online (initial consultation) and can learn and categorize clients’ needs before passing them to the most relevant department, streamlining the processing of new queries.

‍A conversational agent improves engagement as soon as a user visits your website. It can access relevant information faster, and because conversational AI agents ask questions relevant to intake, this helps you qualify leads more effectively with information such as accident details and health information. This also helps your firm decide whether to accept or reject cases faster. Cost is reduced by having less need for human intervention, and time is saved for lawyers and clients. Valuable notes from the conversations allow firms to gain insights into client needs and expectations.

Ambiguity is a significant issue in legal documents. It has the potential to limit intended protections, change terms, and confuse all parties involved. Even the best lawyers can overlook important details that make their contracts less effective.

Soffos' advanced NLP technology can be used to examine a contract with hundreds of pages and complex terms and arrangements. The system can scan these large volumes and identify named entities such as individuals, companies, and references to codes of law. It can flag sections of the document that have contradictions or ambiguities. This kind of system accelerates contract review and negotiation while eliminating human bias, reducing ambiguity, and executing more enforceable contracts by  suggesting revisions for improvement.

Acceleration of contract review, with improved accuracy and decreased risk of ambiguities and contradictions.

Thorough research is essential for all legal processes, but it is also one of the reasons they take so long. Throughout the legal cycle, from filing, to case preparation, to negotiation, extensive research is necessary in order to ensure professionalism and the best possible outcome for clients.

Using Soffos'  NLP platform, this research process can be streamlined and shortened. Internal search engines powered by natural language search can convert plain language searches into "legal language," making it easier to find relevant documents and cases. An NLP solution can also search for high level concepts rather than specific keywords, allowing lawyers to find what they need more quickly.

Saves time and resources improving efficiency.

Market analysts and researchers must sift through massive amounts of documents, articles and reports when they are gathering information on a particular product, company or industry. This often involves a lengthy process of identifying key topics, sorting through many articles that seem to have almost the exact same information, and from that identifying interesting insights or key points of tension and disagreement. The process is time consuming and can be exhausting for researchers.

Using Soffos' advanced technology, a research tool can be created that can pull information from internal and external online sources, and assist in various ways. It can create a "mind map" of topics around a particular search. This mind map can also show visually distant positions on various issues and topics. The system can summarize articles and look for unique information, and researchers can ask direct questions to find answers that may be in certain sources.

With an advanced assistant, researchers can get a much faster high level sense of the area they are researching. They can spend less time sifting through documents reading redundant information, and they can ask direct questions to find specific answers they are looking for, saving time and mental energy.

Salespeople often have a large product portfolio, and the knowledge of these products may be complex, technical and specialized. Their sale may involve regulations or complicated cost estimates. During calls, salespeople may have trouble recalling specific information about specific products that would be relevant and of interest to their prospect, and that may be necessary to successfully closing the sale.

During calls with prospects, questions or comments made during the discussion will trigger live product knowledge suggestions, pulling up information on relevant products, regulations or cost estimates. Salespeople can then review this product knowledge on the spot if they are in need of it, and use it to further guide the discussion with the prospect.

‍When salespeople can pull up information that they need, they can more confidently guide the prospect to the solution that is right for them. This in turn will increase the close ratio, increasing sales revenue.

Salespeople spend hours every day drafting emails, which often include summaries of meeting discussion points and follow-up items. Taking manual notes during a call can distract the salesperson from the live discussion and points may be missed. Recorded call transcripts are long and time-consuming to read through, and drafting an email based on these or on handwritten notes is a time-consuming activity.

‍Calls will be recorded and transcripts created through technology provided by web conferencing software. These call transcripts will then be summarized using an NLP summarization module, making them easier to review. These summaries will then be used as a basis for automatically drafting a follow-up email, which the salesperson can review and make modifications to in minutes, saving hours of time per day.

Time saved by having emails pre-drafted is time that salespeople can be spending on new opportunities. A more efficient sales team means more deals closed and more revenue. Assuming a salesperson spends 30-45 minutes reviewing call notes and drafting a follow-up email, automatic summarization and pre-drafting could reduce that time to 5-10 minutes, saving 1-2 hours per day depending on call volume.

In VR training environments using CBT (Computer-based trainers), the subject often needs to manipulate the simulated training environment to make necessary tweaks and adjustments to improve their skill in their training context (e.g. military, aviation, etc.). While some actions can be completed and confirmed via the motion of the participant, some require decisions or comments. "Interactive buttons" cause major clutter to the virtual reality screens, and are not ideal for confirming these complex tasks.

Using conversational NLP with voice recognition, commands can be given to the machine to confirm complex actions and decisions. This provides easy interaction between the subject and the computer without having to deal with the average clutter you would experience in such an environment, and without having to use hands or eyes, instead, the subject can speak out the command.

Training experience is more clear, more seamless and less overwhelming.

There are news and media sites with more than 160 years' worth of articles. Some of these articles are contained in huge stores of scanned photos of documents. OCR and image classification models can convert these images to text. However, readers and researchers still need efficient and easy ways to find information on topics they are interested in from these mountains of unstructured text.

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Using Soffos' advanced NLP modules, a system can be created to process these millions of articles and make them easily searchable and their content meaningful. NLP can be used to identify entities in each article such as individuals, organizations, dates and laws. Articles can be classified and organized and meaningful topic clusters can be created around groups of documents.

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Readers and researchers will find the site more useful and easy to navigate, encouraging them to find the information that they need there.

News and media sites are in the highly competitive market of keeping and holding their readers' attention. They are looking for ways to responsibly share information, news and analysis as well as respond to reader inquiries. Readers may have questions after reading an article, and if that information is not readily accessible on the page, it will cause them to abandon the site and look for the information elsewhere.

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Using Soffos' advanced NLP modules, news and media sites can create conversation agents to provide readers with the necessary thorough and reliable answers to their questions. These conversational agents can also gather feedback from readers on what they would like to learn more about, how they felt about the article they read, and additional perspectives they are looking for.

Readers will have the opportunity continue engaging with the site that they are on to answer questions that they have, instead of abandoning the site to do an outside search on the topic. They will also have a place to immediately provide feedback on the article and any context that was missing or perspective they felt was missing, reducing churn based on frustration.

Call centers typically deal with very high call volumes, and manage large teams that are fielding these calls. Agents are often dealing with complicated requests, and customers’ various emotional states, often very intense negative ones. Along with these challenges, turnover can be high and newer agents lack experience in company knowledge to answer questions quickly, and the skills to deal with the range of their customers’ emotions.

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Soffos' advanced NLP platform can be used to create a live coaching system for agents. Using voice-to-text transcription, conversations between customer and agent can be captured and analyzed live, identifying topics being discussed, as well as the emotions and intent of the customer. These inputs can then trigger coaching suggestions as well as knowledge to answer questions.

Agents get live coaching support, helping them successfully navigate through challenging situations and to more quickly and successfully resolve customer inquiries, complaints and requests.

One of the most common regularly recurring types of trainings throughout all industries is compliance training. This training is critical to ensure employees are performing their jobs according to company and legal regulations. The challenge is that these regulations change unexpectedly, and small teams of trainers are often responsible for huge numbers of employees, who don't necessarily find the material interesting, and often forget it as soon as training sessions are completed.

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Soffos' advanced NLP platform can be used to automatically pull updated regulatory information from online sites, software, and other communications from relevant authorities. This information can then be summarized, automatically shared, or used to create micro-lessons for employees to interact with. Soffos' platform can also be used to create automatic mini-quizzes on a regular basis, keeping information fresh in the mind of employees and identifying knowledge gaps.

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Training sessions and assessments can be created quickly and with minimal effort, allowing team leaders to adequately train large employee populations. Training material will also be up to date, consistently keeping with quickly changing requirements.

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The COVID-19 pandemic hugely shifted the ratio of in-office vs remote employees, and this shift continued in many cases even post-pandemic. This increased the amount of training sessions that are now carried out online vs in person. It is especially challenging to keep trainees engaged in the material when it's online. In general, for L&D executives It is a challenge to measure the engagement and the effectiveness of courses online, and there are additional difficulties with this in live training courses.

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Soffos' NLP modules can be used to create transcripts of live lectures and to automatically create Q&A flashcards to test learners in real time. A conversational agent can also be available during the training to answer questions which trainees may be hesitant to ask out loud. A dashboard can track and display information about the learner's attention and retention, detect knowledge gaps, and determine the course's effectiveness which will support L&D executives in their decision-making.

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Live assessments keep employees engaged and interested, and hold employees accountable for absorbing the knowledge being presented to them. Tracking the effectiveness of the course will aid in the improvement of training quality, resulting in better business processes.

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One of the most difficult challenges for L&D executives is keeping their employees up to date in a rapidly changing tech and organizational environment - especially with limited training budgets and resources. In areas such as compliance and product knowledge, material is often changing, and trainings can become outdated almost as soon as they are created.

Using Soffos' smart platform, create a knowledge management system to ingest files in any text, video or audio formats and that automatically detects changes and updates to previous materials.  Employees can be notified of changes, micro lessons on the new material can be automatically created, and employees can ask questions using conversational AI anytime they are unsure of the most up-to-date information.

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Training courses will be reduced to the minimum - reducing training costs, saving time, resources and improving employee experience.

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While eLearning is scalable and relatively inexpensive, it lacks the ability to provide feedback, clarity and expansion on curriculum topics often needed by the student. Students have questions about the material but have nowhere to turn for answers. Even in cases where feedback is possible, students may have questions that they are embarrassed to ask if they believe they should already know the answer, and after taking the course, they might want to check on information that has changed or been updated.

Soffos' smart platform provides a virtual coach or mentor who can answer questions, provide feedback, and who can ask further questions to test the user. The exchange is in addition to the core body of information in the eLearning course, and supplemental definitions and information can be gathered from various curriculum sources.

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Support for students without requiring additional FTEs to assist a percentage of students that may need additional training content and explanation.

In the maritime industry, there are typically huge volumes of training and other important sources of knowledge important for safety, compliance and proper operations. At the same time, many crew members are not often in front of a computer, and beyond initial training and assessment at the start of employment, it remains difficult for trainers to know how much knowledge has been retained and to have continuous re-training sessions. This is made even more challenging by high turnover rates.

Using Soffos' advanced platform, large volumes of knowledge and training material can be easily ingested and normalized. A conversational AI chatbot can be set up so that crew members can ask questions anytime they feel unsure about a topic or procedure. A QR code can be set up in a convenient location where crew members can scan it to access the chatbot. Quizzes can also be automatically generated on a regular basis, so that training sessions are better retained and knowledge gaps identified.

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Training and assessment is easierto implement and access, leading to better performing crew members.

During installation and/or repair procedures, access to reference materials, settings, and other information is cumbersome as a mechanic's hands are usually occupied holding parts or executing steps in a task.

Soffos' natural language processing platform can be used for voice commands and questions combined with AR visual recognition (where needed) to assist/guide a mechanic through the steps of a repair or installation procedure.

The benefits include better efficiency, reduced errors, faster onboarding of new technicians and mechanics, and the potential for extending the data interface to include the onboard computation modules for many modern machines.