See you this Sunday at ACA International’s #ACACONV24 in San Diego! We’ll be at booth #317! Eddie Mele Ajay Nair Vivian Danny
Skit.ai
Software Development
Leading Conversational AI solution. One Platform for Multichannel Collections Conversations powered by Generative AI
About us
Skit.ai is the leading Conversational AI company in the accounts receivables industry, empowering collection agencies and creditors to automate collection conversations and accelerate revenue recovery. Skit.ai’s suite of multichannel solutions—featuring voice, text, email, and chat, in both English and Spanish, powered by Generative AI—interacts with consumers in their preferred channel, elevating consumer experiences and consequently boosting recoveries.
- Website
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https://bit.ly/3Na9CoG
External link for Skit.ai
- Industry
- Software Development
- Company size
- 201-500 employees
- Headquarters
- New York
- Type
- Privately Held
- Founded
- 2016
- Specialties
- Artificial Intelligence, Deep Learning, Natural Language Processing, Customer-first Approach, B2B, SAAS, Automation, Product, Business Operations, CSAT, Enterprise, Enterprise Software, India, United States, Analytics, Call Automation, Inbound, Outbound, Collections, ARM Industry, Multichannel, ConversationalAI, AI, SMS , and Chatbot
Locations
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Primary
135 Madison Avenue, 6th Floor, NY
New York, 10016, US
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Krishvi Aspire, 4th Floor, 516
Chinmaya Mission Hospital Rd, Binnamangala, Stage 1, Indiranagar
Bengaluru, Karnataka 560038, IN
Employees at Skit.ai
Updates
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Delinquencies are rising among younger consumers. The same consumers who are least likely to respond to your print letters. However, you can reduce delinquencies and optimize your collection strategy with Skit.ai. Get in touch with one of our experts today and learn more: https://lnkd.in/etW-WVFj #ConversationalAI #DebtCollection #ARMIndustry #AccountsReceivable #DebtRecovery #ARM #ConversationalAI #Chatbot #SMSBot #Multichannel #MultichannelAI #CollectionAgencies #DelinquentAccounts
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Many Healthcare RCM providers and divisions struggle to consistently implement early-out collections due to resource constraints. With rising attrition and thinning profit margins, it's too easy to miss collection opportunities. Conversational AI offers a scalable solution to automate early-out collections. By contacting patients promptly and courteously after sending a bill, early-out practices encourage timely payments. This approach can significantly enhance cash flow and improve the patient experience. Read our blog to learn more: https://lnkd.in/eV23wDfN #RevenueCycleManagement #ConversationalAI #IntelligentAutomation #MedicalBilling #AIinHealthcare #InnovationInHealthcare #HealthTech #PatientExperience #HealthcareAutomation
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Take a look at the July issue of our accounts receivables newsletter! Subscribe for monthly updates on industry news, events, and webinars. 🗞
DEBTox July 2024: Chatbots Are the Future
Skit.ai on LinkedIn
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Implementing Conversational AI for collection agencies involves the crucial step of exchanging account data with CRMs. Read our blog to learn how we’ve overcome the challenge of seamless CRM integration: https://lnkd.in/gQq27J-R #ConversationalAI #DebtCollection #DebtRecovery #ARMIndustry #AccountsReceivable #ARM #MultichannelAI #RPABot #CRMIntegrations #NoCodeIntegration
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The adoption of High Deductible Healthcare Plans (HDHPs) are increasing, leading to a rise in self-pay dues. This trend poses a serious challenge for Healthcare RCM providers. Their limited scalability and agent unavailability for early-out collections make it difficult to collect larger dues and manage more accounts effectively. Read our blog to understand why HDHPs are on the rise, the implications for RCM providers, and the only viable solution for overcoming these challenges: https://lnkd.in/g6dGBpzj #ConversationalAI #HealthcareCollections #DebtCollection #DebtRecovery #ARMIndustry #AccountsReceivable #ARM #MultichannelAI #RCMCompanies #RevenueCycleManagement #PatientCollections #EarlyOutCollections
Impact of HDHPs on Early-Out Collections for RCM Providers
https://skit.ai
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Collection agencies rely on credit scores to assess consumers' creditworthiness, but these scores have significant limitations: a) They are based on limited credit lending history, leading to biases against consumer segments with minimal credit records. b) They lack detailed data on consumer behavior, such as the optimal time to contact a consumer for effective engagement. #LargeLanguageModels (LLMs), trained with proprietary data and past agent interactions, can bridge these gaps. LLMs can reduce biases and help collection agencies determine the best engagement and recovery strategies at an individual level. Skit.ai’s Generative AI technology can: - Reduce biases against specific consumer segments with limited credit histories. - Help determine the best engagement strategy for each account. Read the latest oped by our CEO, Sourabh Gupta: https://lnkd.in/diG73Jki #ConversationalAI #LargeLanguageModel #LLMBots #DebtCollection #DebtRecovery #ARMIndustry #AccountsReceivable #ARM #MultichannelAI #AutoFinance #AutoCollections
Generative AI Is More Powerful Than We Realize
insidearm.com
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To mark the conclusion of #PrideMonth, today our team participated in a fun scavenger hunt about the importance of celebrating LGBTQ history and identities! 🌈
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Exciting news from our ML research team!
We at Skit.ai are thrilled to announce the release of our latest Multi-Modal LLM models for Speech Understanding on Hugging Face, along with a comprehensive GitHub repository containing the code to train and infer these models! Unlike traditional ASR + LLM systems, our multi-modal speech LLMs leverage the acoustic, semantic, prosodic, and speaker information in the speech signal to predict various attributes such as Transcript, Speech Activity, Gender, Age, Accent, and Emotion of the speaker in a conversation directly from the speech signal. The models can be further trained to generate responses based on the user's metadata in an end-to-end manner for TOD systems, eg: Apologetic responses, when the speaker appears frustrated, etc. Similar to our previous demo blog on Multi-Modal LLM for Conversational Agents - https://lnkd.in/gRaSi99X. Due to the simplicity of training the model, any new perception/generation tasks could be added to the model eg: Multi-speaker transcript, speech environment classification, speech translation, etc. 🔗 Check it out: Hugging Face Models: • speechllm-2B: https://lnkd.in/gdRAwj3U • speechllm-1.5B: https://lnkd.in/gdGA6Jzj GitHub Repository: https://lnkd.in/gu6DSvmc #MultiModalLLM #LLM #HuggingFace #GitHub #ConversationalAI
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