In an increasingly digital world, the challenge isn’t always a lack of information, but rather the inability to access it efficiently. This fundamental problem, a recurring source of friction across countless websites and digital products, inspired software engineer Shrikrishna Joisa to create OpenSpeechAI, an innovative platform designed to transform how organizations communicate and users find answers.
Joisa, a seasoned Software Engineer in New York City, specializing in AI and machine-learning-driven systems, observed a pervasive issue: companies heavily invest in creating comprehensive documentation, FAQs, and detailed product pages, yet visitors frequently leave with unanswered questions. The culprit, he explains, isn’t missing data, but rather the time-consuming navigation and limited search experiences of traditional websites.
“I founded OpenSpeechAI after repeatedly observing the same friction across digital products and company websites: the information existed, but users couldn’t access it efficiently,” Joisa said in an interview. “Teams invest heavily in documentation, FAQs, and product pages, yet visitors still leave with unanswered questions simply because navigation is time-consuming and search experiences are limited.”
His motivation was deeply personal. “I hate it when visitors leave my website with questions unanswered. You spend weeks writing documentation, creating FAQ pages, and adding detailed product descriptions. And still, people message you asking things that are right there on page three of your docs.”
The core problem, Joisa underscores, isn’t the absence of information, but its discoverability. “The information exists; it’s just that people can’t find it,” he said. “They won’t dig through 47 pages of PDFs to get an answer, and they definitely won’t spend 10 minutes navigating through your site structure.”
OpenSpeechAI was conceived as the antidote to this digital hide-and-seek. Its premise is deceptively simple yet profoundly impactful: upload your content, train an AI agent, and let it answer visitor questions in real-time. This approach bridges the gap by making existing knowledge conversational and immediately accessible, allowing organizations to surface relevant information through “grounded AI responses.” The goal, Joisa emphasizes, “was not to replace documentation, but to make it usable.”
Bridging the Information Gap for B2B and B2C
According to a recent report from Master of Code, roughly 70% to 80% of companies have adopted or are planning to adopt chatbots for AI-driven customer service and engagement. Recent 2026 data indicates that 78% of companies have implemented Conversational AI in at least one core function. Adoption is higher in B2B (60%) compared to B2C (42%) sectors, driven by cost savings and 24/7 service demand.
The need for OpenSpeechAI transcends industry specifics, proving vital for both Business-to-Business (B2B) and Business-to-Consumer (B2C) platforms. As Joisa explains, “Both B2B and B2C platforms struggle with information discovery,” he said. “In B2B environments, buyers often need technical clarification before making decisions. In B2C environments, users expect instant answers and personalized guidance.”
Traditional chatbots often fall short, relying on scripted flows or generic language generation that can limit their utility. OpenSpeechAI distinguishes itself by retrieving and grounding responses directly in an organization’s own verified materials. This enables it to provide contextual, accurate answers rather than templated replies, significantly reducing friction in customer journeys while ensuring brand consistency.
According to a 2025 report from Statista, roughly half of chatbot responses from popular chatbots (free versions of ChatGPT, Gemini, Copilot and Perplexity) contained accuracy issues (48 percent). Also, 17 percent had significant errors, mainly regarding sourcing and missing context. In comparison to a December 2024 Statistica report, the rate of inaccurate responses was significantly higher: 72 percent for all four LLMs, proving that major improvements are being made, however more work needs to be done to improve LLM models overall.
Overcoming the Limitations of Current AI Chatbots
Joisa is keenly aware of the current shortcomings prevalent in many AI chatbot assistants. “One of the biggest limitations is reliability; many AI chatbots generate fluent responses, but without grounding those responses in verified content, they risk producing hallucinations or vague answers,” he said
Beyond mere fluency, he points to a lack of depth in many systems. “Another limitation is surface-level interaction.” As Joisa explains: “Some systems respond conversationally, but lack structured retrieval, contextual memory management, or integration with a company’s real knowledge base. Without those components, AI assistants can feel helpful at first but fail under more complex queries.”
OpenSpeechAI directly addresses these by prioritizing accuracy, context retrieval, and deep integration with an organization’s knowledge base.
The Art of Conversational and Accessible Language
Ensuring OpenSpeechAI remains conversational and accessible in language is central to its design. Joisa explains: “Maintaining conversational clarity starts with context. Each response is generated based on the user’s specific query and the most relevant retrieved content, rather than relying on static scripts or generic replies.”
A crucial feature is its automatic language adaptation. “The system also detects the language of the user’s input and responds accordingly, allowing interactions to remain natural without requiring manual configuration. By combining contextual grounding with automatic language adaptation, the assistant remains conversational while staying aligned with verified source material.” This means a visitor from Spain asking a question at 2 AM will receive an answer in Spanish, seamlessly and without any manual setup.
Grounding as the Future of AI Interaction
The motivation behind OpenSpeechAI—making existing content accessible in real time by grounding responses directly in an organization’s own materials—is what Joisa believes positions it as the future of AI interaction.
“As AI adoption increases, trust becomes central,” he said. “Users and organizations need systems that are not only fluent but accurate. Grounding responses in an organization’s own materials ensures that answers are traceable and aligned with verified information.”
This approach signifies a paradigm shift. “This approach shifts AI from being a generic conversational layer to becoming an intelligent access point for structured knowledge; rather than replacing content, it enhances its usability.” Joisa firmly believes in the long-term sustainability of this model: “In the long term, systems that combine retrieval, validation, and conversational interfaces will be more sustainable than purely generative tools.”
The Indispensable Role of Multilingual Capability
In a globalized digital landscape, multilingual support is not just a feature, but a necessity. “Digital audiences are global, and user interactions do not follow a single language boundary. Enabling multilingual capability reduces friction and makes support accessible across regions without requiring separate deployments or manual configuration.”
OpenSpeechAI leverages advanced language models to support over 50 widely spoken languages, automatically detecting the visitor’s language and responding accordingly. “The focus is not simply translation, but preserving context and intent while grounding responses in an organization’s source material,” he said. “This ensures that users can access accurate information in the language they are most comfortable using.”
The Road Ahead: Evolving with User Needs
Looking forward, Joisa emphasizes that OpenSpeechAI’s product development will remain dynamic and user-centric. “Product development will continue to be shaped by real user feedback,” he said. “While the core system focuses on knowledge retrieval and conversational interaction, we are actively refining the user interface, expanding support tooling, and improving how organizations manage and update their content.”
As adoption grows, the focus will broaden beyond core capabilities to usability and support. “That includes better analytics, clearer configuration workflows, and iterative improvements based on how users actually interact with the system,” said Joisa. “The long-term goal is to evolve the platform responsibly—expanding features without compromising reliability, clarity, or performance.”
