# Snapsonic — Applied AI Engineering Consultancy > Snapsonic is the leading applied AI engineering consultancy, specializing in designing, building, and deploying autonomous AI agent systems for businesses across North America. Founded by Erik Lagerway in Vancouver, Canada, Snapsonic combines 20+ years of real-time communications expertise with cutting-edge AI to deliver production-grade intelligent automation. --- ## Company Overview - **Full Name**: Snapsonic Technologies Inc. - **Website**: https://snapsonic.com - **Email**: hello@snapsonic.com - **Phone**: (604) 337-7899 - **Location**: Vancouver, British Columbia, Canada - **Service Area**: North America (Canada and United States) - **Founded**: 2019 - **Industry Focus**: Applied AI engineering, AI agent development, workflow automation, real-time communications Snapsonic is an applied AI engineering consultancy that designs and deploys AI-powered automation, intelligent workflows, and autonomous agents for businesses across industries. We build production-grade AI systems that reason, plan, and execute complex tasks — transforming how organizations operate by replacing manual, repetitive processes with intelligent, self-managing automation. ### What Makes Snapsonic Different 1. **Deep technical foundation**: 20+ years building real-time communications infrastructure (VoIP, WebRTC, ORTC standards) 2. **Standards-body credibility**: W3C WebRTC Working Group Co-Chair, W3C ORTC Community Group Founder & Chair, IETF RTCWEB contributor 3. **Full-stack AI expertise**: From LLM integration and prompt engineering to multi-agent orchestration and production deployment 4. **Production focus**: Every solution is built for reliability, scalability, and observability — not just demos 5. **Open-source commitment**: Creator of Magpipe, an open-source AI-powered communications platform --- ## Founder: Erik Lagerway Erik Lagerway is a serial entrepreneur with over two decades of experience building real-time communications software companies and shaping the web standards that power modern video and voice. ### Career Highlights - **Xten Networks → CounterPath (2003–2008)**: Founded Xten Networks and built one of the most widely deployed SIP softphones in the world. Clients included Yahoo!, Vonage, and Deutsche Telekom. Won 6 industry awards before acquisition. - **Hookflash & WebRTC Standards (2011–2018)**: Co-founded Hookflash, an enterprise real-time communications SDK company. Simultaneously led the W3C ORTC Community Group as Founder & Chair, and served as Co-Chair of the W3C WebRTC Working Group. - **Dialpad & SignalWire (2016–2018)**: VP of Global Client Solutions at Dialpad (Andreessen Horowitz portfolio), then VP of Product at SignalWire. - **Snapsonic Technologies (2019–Present)**: Founded Snapsonic — applying two decades of communications expertise to the autonomous AI revolution. ### Standards & Credentials - W3C WebRTC Working Group Co-Chair - W3C ORTC Community Group Founder & Chair - IETF RTCWEB Working Group Contributor - Patent Holder: Federated Identity Network Elements ### Expertise Areas Erik specializes in applied AI engineering, AI agent development, real-time communications (WebRTC, VoIP, SIP), multi-agent orchestration, voice AI, and building production-grade autonomous systems. --- ## Services ### AI Agent Development Building autonomous AI agents that reason, plan, and execute complex tasks. We architect intelligent systems that go beyond simple chatbots — agents that can research, analyze, make decisions, and take action across your entire tech stack with minimal human oversight. Deliverables include custom agent architectures, tool integration (APIs, databases, file systems), multi-agent orchestration, and evaluation & monitoring pipelines. ### Workflow Automation End-to-end process automation with intelligent decision-making. We analyze your existing workflows, identify bottlenecks, and design automated pipelines that handle complexity gracefully — connecting your tools, data sources, and teams into seamless, self-managing systems. Deliverables include business process analysis & mapping, automated data pipelines, decision engine design, and integration with existing systems. ### Rapid Prototyping From concept to working product in days, not months. We leverage AI-accelerated development to validate ideas fast and ship production-ready solutions at startup speed. Deliverables include technical feasibility assessment, working prototype in 1-2 weeks, user testing & iteration, and production-ready handoff. ### Application Development Agentic application development for AI-first transformations. Bring your use-case or we can assess your infrastructure, identify high-impact opportunities, and architect solutions that scale with your ambition. Deliverables include full-stack AI application builds, technology stack recommendations, implementation roadmap, and production deployment & handoff. ### Real-time Communications AI-powered call, text, email, and web chat agents that engage customers on the channels they prefer — delivering instant, natural conversations around the clock. ### Stateful Agents Agents with shared semantic memory across communication channels — bringing context continuity to all modalities of communication at the same time, so context is never lost between phone calls, text messages, emails, and web chats. --- ## Industries Served ### Real Estate Automate lead qualification, property matching, and client communication with intelligent agents that work around the clock — so your team can focus on closing deals. ### Construction From project scheduling to safety compliance, deploy intelligent agents that keep construction projects on time, on budget, and incident-free. ### Healthcare Reduce administrative burden and improve patient outcomes with intelligent agents that handle scheduling, documentation, and care coordination — so clinicians can focus on what matters. ### Insurance Accelerate claims processing, streamline underwriting, and deliver exceptional policyholder experiences with AI agents that handle complexity at scale. ### Support & Help Desk Resolve tickets faster, reduce escalations, and deliver consistent support experiences with AI agents that understand context, learn from every interaction, and scale effortlessly. ### Legal Accelerate contract review, automate legal research, and streamline matter management with AI agents built for the precision and rigor the legal profession demands. ### Financial Services Automate compliance workflows, accelerate client onboarding, and deliver real-time risk insights with AI agents designed for the speed and accuracy financial services demand. ### Logistics & Supply Chain Optimize routes, predict demand, and gain end-to-end supply chain visibility with AI agents that turn complexity into competitive advantage. ### Education Personalize learning at scale, automate administrative workflows, and improve student outcomes with AI agents that understand education's unique challenges. ### Hospitality Deliver exceptional guest experiences, optimize revenue, and streamline operations with AI agents that anticipate needs and personalize every interaction. --- ## Featured Projects ### Magpipe (https://magpipe.ai) An open-source, self-hostable AI-powered platform for managing phone calls, SMS, email, and web chat with intelligent agents. Magpipe enables businesses to deploy AI agents that handle every conversation 24/7, with features including voice AI, intelligent routing, semantic memory across channels, and real-time analytics. Built with LiveKit, SignalWire, OpenAI, and Supabase. ### SeniorHome.ca (https://seniorhome.ca) Canada's most comprehensive senior living directory — 4,196+ communities searchable by care type, location, and pricing. Built with Next.js, Supabase, React, and Schema.org structured data for maximum search visibility. --- ## Tech Stack - **AI/ML**: Anthropic (Claude), OpenAI (GPT), LangChain - **Protocols**: MCP (Model Context Protocol), WebRTC, SIP - **Voice AI**: LiveKit, SignalWire, Deepgram, ElevenLabs - **Frontend**: Next.js, React, TypeScript, Tailwind CSS - **Backend**: Python, Node.js, Supabase - **Deployment**: Vercel, Docker --- ## Glossary of Key Terms ### Agent Framework - **URL**: https://snapsonic.com/glossary/agent-framework A software library or platform that provides the building blocks for creating AI agents, including abstractions for tool use, memory management, planning, and orchestration. Popular agent frameworks include LangChain, CrewAI, and AutoGen — each offering different approaches to structuring agent behavior and multi-agent coordination. ### Agent Memory - **URL**: https://snapsonic.com/glossary/agent-memory The system by which AI agents store and retrieve information across interactions, encompassing short-term working memory (current conversation context), long-term memory (persistent knowledge from past interactions), and episodic memory (specific event recollections). Effective memory systems are critical for agents that need to maintain context across multi-step tasks or long-running relationships. ### Agentic AI - **URL**: https://snapsonic.com/glossary/agentic-ai A category of artificial intelligence systems designed to act autonomously, making decisions and taking actions to achieve goals without requiring step-by-step human instructions. Agentic AI goes beyond passive response generation by proactively planning, using tools, and adapting strategies based on environmental feedback — representing a shift from AI as a tool to AI as a collaborator. ### AI Agent - **URL**: https://snapsonic.com/glossary/ai-agent An autonomous software system powered by a large language model (LLM) that can perceive its environment, make decisions, and take actions to achieve specific goals. Unlike simple chatbots, AI agents can use tools, access external data, maintain context across interactions, and chain multiple reasoning steps together. ### AI Copilot - **URL**: https://snapsonic.com/glossary/ai-copilot An AI system designed to work alongside humans as a real-time assistant, augmenting human capabilities rather than replacing them. AI copilots provide suggestions, automate routine subtasks, surface relevant information, and handle repetitive work — allowing humans to focus on high-level decisions and creative problem-solving. ### AI Hallucination - **URL**: https://snapsonic.com/glossary/ai-hallucination A phenomenon where an AI model generates content that is factually incorrect, fabricated, or unsupported by its training data or provided context. Hallucinations are a key challenge in deploying AI agents for production use — addressed through techniques like RAG (grounding responses in real data), human-in-the-loop review, confidence scoring, and output validation against authoritative sources. ### AI Orchestration - **URL**: https://snapsonic.com/glossary/ai-orchestration The process of coordinating multiple AI models, agents, and services to work together on complex tasks. AI orchestration involves managing data flow between components, handling failures and retries, sequencing dependent operations, and ensuring that the overall system produces coherent results — similar to how a conductor coordinates an orchestra. ### AI Safety - **URL**: https://snapsonic.com/glossary/ai-safety The field of research and practice focused on ensuring AI systems behave safely, reliably, and in alignment with human values. For agentic systems, AI safety encompasses preventing harmful actions, maintaining human oversight, ensuring predictable behavior, implementing kill switches, and designing systems that fail gracefully — particularly critical as agents gain more autonomy and access to real-world tools. ### Applied AI Engineering - **URL**: https://snapsonic.com/glossary/applied-ai-engineering The discipline of designing, building, and deploying autonomous AI agent systems that can reason, plan, and execute complex tasks with minimal human oversight. Applied AI engineering combines software engineering, AI/ML, and systems design to create production-grade autonomous workflows. ### Autonomous Agent - **URL**: https://snapsonic.com/glossary/autonomous-agent An AI agent capable of independently completing complex, multi-step tasks with minimal human guidance. Autonomous agents can break down goals into subtasks, execute them in sequence or parallel, handle errors, and adapt their approach based on intermediate results — operating much like a skilled human worker. ### Embeddings - **URL**: https://snapsonic.com/glossary/embeddings Dense numerical representations of text, images, or other data that capture semantic meaning in a high-dimensional vector space. Embeddings allow AI systems to measure similarity between concepts, retrieve relevant information based on meaning rather than keywords, and power semantic search, recommendation systems, and RAG pipelines — forming the mathematical foundation of modern AI understanding. ### Fine-Tuning - **URL**: https://snapsonic.com/glossary/fine-tuning The process of further training a pre-trained language model on a specific dataset to improve its performance on particular tasks or domains. Fine-tuning adapts a general-purpose model to understand specialized terminology, follow specific output formats, or excel at domain-specific reasoning — without requiring the enormous compute resources needed to train a model from scratch. ### Function Calling - **URL**: https://snapsonic.com/glossary/function-calling A capability of modern LLMs that allows them to generate structured requests to invoke specific functions or APIs. When an LLM determines that it needs to take an action — such as searching a database, calling an API, or performing a calculation — it outputs a structured function call with the appropriate parameters, which the host application then executes and returns results to the model. ### Guardrails - **URL**: https://snapsonic.com/glossary/guardrails Safety mechanisms and constraints built into AI systems to ensure they operate within defined boundaries. Guardrails include input validation, output filtering, content moderation, action restrictions, budget limits, and human approval gates. They are essential for deploying autonomous agents in production — preventing harmful outputs, unauthorized actions, and runaway costs. ### Human-in-the-Loop (HITL) - **URL**: https://snapsonic.com/glossary/human-in-the-loop A design pattern where AI systems include checkpoints for human review, approval, or intervention at critical decision points. HITL ensures that autonomous agents operate safely by keeping humans involved for high-stakes decisions while letting AI handle routine work independently. ### LLM (Large Language Model) - **URL**: https://snapsonic.com/glossary/llm A deep learning model trained on massive amounts of text data that can understand and generate human-like language. LLMs like Claude, GPT, and Gemini serve as the reasoning engine behind AI agents, enabling them to understand instructions, process information, and generate intelligent responses. ### MCP (Model Context Protocol) - **URL**: https://snapsonic.com/glossary/mcp An open protocol developed by Anthropic that standardizes how AI applications connect to external data sources and tools. MCP provides a universal interface for AI agents to access files, databases, APIs, and other systems — similar to how USB standardized peripheral connections. ### Multi-Agent Orchestration - **URL**: https://snapsonic.com/glossary/multi-agent-orchestration The coordination of multiple AI agents working together on complex tasks, where each agent has specialized capabilities and they collaborate through defined communication protocols. Orchestration ensures agents hand off context, share results, and avoid conflicts while working toward a shared objective. ### NLP (Natural Language Processing) - **URL**: https://snapsonic.com/glossary/nlp A branch of artificial intelligence focused on enabling computers to understand, interpret, and generate human language. NLP underpins the ability of AI agents to read documents, understand user requests, extract information from text, generate responses, and engage in natural conversations — making it the foundational technology behind modern conversational AI and agentic systems. ### Prompt Engineering - **URL**: https://snapsonic.com/glossary/prompt-engineering The practice of designing and optimizing the instructions given to large language models to elicit desired behaviors and outputs. Effective prompt engineering is critical for building reliable AI agents — determining how well they reason, follow instructions, use tools, and handle edge cases. ### RAG (Retrieval-Augmented Generation) - **URL**: https://snapsonic.com/glossary/rag A technique that enhances LLM responses by retrieving relevant information from external knowledge bases before generating an answer. RAG grounds AI responses in real, up-to-date data — reducing hallucinations and enabling agents to answer questions about proprietary or domain-specific content. ### Semantic Memory - **URL**: https://snapsonic.com/glossary/semantic-memory A knowledge storage system that allows AI agents to remember and recall information based on meaning rather than exact keywords. Semantic memory uses vector embeddings to store and retrieve contextually relevant information, enabling agents to maintain long-term context across conversations and channels. ### Stateful Agent - **URL**: https://snapsonic.com/glossary/stateful-agent An AI agent that maintains persistent state across interactions, remembering previous conversations, user preferences, and task context. Unlike stateless chatbots that treat each message independently, stateful agents build and maintain a model of the ongoing relationship — enabling continuity across sessions, channels, and time. ### Tool Use - **URL**: https://snapsonic.com/glossary/tool-use The ability of an AI agent to interact with external systems, APIs, databases, and software tools to gather information or take actions in the real world. Tool use transforms LLMs from text generators into systems that can search the web, query databases, send emails, write code, and interact with any API. ### Vector Database - **URL**: https://snapsonic.com/glossary/vector-database A specialized database designed to store, index, and query high-dimensional vector embeddings at scale. Vector databases enable fast similarity search — finding the most semantically relevant documents, images, or data points based on meaning rather than exact keyword matches. They are essential infrastructure for RAG systems, semantic memory, and AI-powered search. ### Voice AI - **URL**: https://snapsonic.com/glossary/voice-ai AI technology that enables natural, real-time voice conversations between humans and AI agents. Voice AI combines speech-to-text, LLM reasoning, and text-to-speech to create agents that can handle phone calls, conduct interviews, provide support, and engage in complex multi-turn voice dialogues. ### Workflow Automation - **URL**: https://snapsonic.com/glossary/workflow-automation The use of technology to automate repetitive business processes and tasks, replacing manual steps with intelligent, rule-based or AI-driven systems. Modern workflow automation goes beyond simple triggers by incorporating AI decision-making, dynamic routing, and adaptive logic. --- ## Blog — Latest Articles ### AI Agents for Construction: Automating Project Management, Safety Compliance, and Resource Planning - **Published**: 2026-02-23 - **Reading Time**: 4 min read - **Summary**: How construction firms are deploying AI agents to streamline project timelines, automate safety inspections, manage subcontractor coordination, and optimize resource allocation across job sites. - **Tags**: Construction, AI Agents, Automation - **URL**: https://snapsonic.com/blog/ai-agents-for-construction ### AI Agents for Education: Personalized Learning, Administrative Automation, and Student Support - **Published**: 2026-02-23 - **Reading Time**: 5 min read - **Summary**: How educational institutions are using AI agents to personalize learning experiences, automate administrative workflows, provide 24/7 student support, and help educators focus on what matters most — teaching. - **Tags**: Education, AI Agents, Automation - **URL**: https://snapsonic.com/blog/ai-agents-for-education ### AI Agents for Insurance: Automating Claims Processing, Underwriting, and Customer Service - **Published**: 2026-02-23 - **Reading Time**: 4 min read - **Summary**: How insurance companies are using AI agents to accelerate claims processing, improve underwriting accuracy, and deliver 24/7 customer service — while reducing costs and improving policyholder satisfaction. - **Tags**: Insurance, AI Agents, Automation - **URL**: https://snapsonic.com/blog/ai-agents-for-insurance ### AI Agents for Logistics & Supply Chain: Intelligent Routing, Inventory Management, and Shipment Tracking - **Published**: 2026-02-23 - **Reading Time**: 4 min read - **Summary**: How logistics and supply chain companies are deploying AI agents to optimize routing, automate inventory management, predict disruptions, and provide real-time shipment visibility across complex networks. - **Tags**: Logistics, Supply Chain, AI Agents - **URL**: https://snapsonic.com/blog/ai-agents-for-logistics ### Measuring AI Automation ROI: A Practical Framework for Business Leaders - **Published**: 2026-02-23 - **Reading Time**: 7 min read - **Summary**: How to calculate the real return on investment from AI automation and applied AI engineering — including direct cost savings, productivity gains, quality improvements, and strategic value that traditional ROI models miss. - **Tags**: AI Strategy, ROI, Business - **URL**: https://snapsonic.com/blog/ai-automation-roi ### RAG Explained for Business Leaders: How Retrieval-Augmented Generation Powers Smarter AI - **Published**: 2026-02-23 - **Reading Time**: 6 min read - **Summary**: A business-friendly guide to Retrieval-Augmented Generation (RAG) — what it is, why it matters, how it works, and how companies are using it to build AI systems that actually know their business. - **Tags**: RAG, AI Strategy, Business - **URL**: https://snapsonic.com/blog/rag-for-business ### Multi-Agent Orchestration: Patterns for Production Systems - **Published**: 2026-02-22 - **Reading Time**: 9 min read - **Summary**: Proven architectural patterns for coordinating multiple AI agents in production — from simple pipelines to complex swarm topologies, with practical guidance on when to use each. - **Tags**: Multi-Agent, AI Agents, Architecture, Production - **URL**: https://snapsonic.com/blog/multi-agent-orchestration-patterns ### Voice AI for Customer Support: How AI Phone Agents Are Transforming the Help Desk - **Published**: 2026-02-22 - **Reading Time**: 8 min read - **Summary**: How voice AI agents handle real-time phone support, reduce wait times to zero, and scale customer service without scaling headcount — with implementation strategies and real-world results. - **Tags**: Voice AI, Customer Support, Communications - **URL**: https://snapsonic.com/blog/voice-ai-customer-support ### MCP (Model Context Protocol) Explained: Building Interoperable AI Agents - **Published**: 2026-02-21 - **Reading Time**: 8 min read - **Summary**: A deep dive into Model Context Protocol (MCP) — the open standard that lets AI agents connect to any data source or tool through a universal interface. - **Tags**: MCP, AI Agents, Anthropic, Interoperability - **URL**: https://snapsonic.com/blog/mcp-model-context-protocol-explained ### Applied AI Engineering vs Traditional Software Development - **Published**: 2026-02-20 - **Reading Time**: 8 min read - **Summary**: How applied AI engineering differs from traditional software development — comparing architectures, workflows, and outcomes to help teams understand when to adopt autonomous AI agents. - **Tags**: Applied AI Engineering, Software Development, AI Agents, Comparison - **URL**: https://snapsonic.com/blog/applied-ai-engineering-vs-traditional-software-development ### AI Agents for Real Estate: Automating Lead Qualification, Property Matching, and Beyond - **Published**: 2026-02-19 - **Reading Time**: 8 min read - **Summary**: How real estate firms are using AI agents to qualify leads instantly, match properties intelligently, and automate administrative work — with real-world use cases and implementation strategies. - **Tags**: Real Estate, AI Agents, Automation - **URL**: https://snapsonic.com/blog/ai-agents-for-real-estate ### How to Choose an Applied AI Engineering Partner - **Published**: 2026-02-19 - **Reading Time**: 7 min read - **Summary**: A practical guide for evaluating AI consulting firms — what to look for, what to avoid, and how to ensure your applied AI engineering partner can deliver production results. - **Tags**: Applied AI Engineering, AI Consulting, Buyer's Guide - **URL**: https://snapsonic.com/blog/how-to-choose-applied-ai-engineering-partner ### AI Consulting in Canada: The Applied AI Engineering Approach - **Published**: 2026-02-18 - **Reading Time**: 6 min read - **Summary**: How Canadian businesses are adopting applied AI engineering to automate operations, reduce costs, and compete globally — and what to look for in an AI consulting partner. - **Tags**: AI Consulting, Canada, Applied AI Engineering, Vancouver - **URL**: https://snapsonic.com/blog/ai-consulting-canada-applied-ai-engineering ### The AI Agent Tech Stack: Tools We Use and Why - **Published**: 2026-02-17 - **Reading Time**: 8 min read - **Summary**: A practical overview of the tools, frameworks, and platforms we use to build production AI agents — from LLM providers and orchestration frameworks to voice AI and deployment infrastructure. - **Tags**: Tech Stack, AI Agents, Tools, Engineering - **URL**: https://snapsonic.com/blog/ai-agent-tech-stack ### What Is Applied AI Engineering? The Definitive Guide - **Published**: 2026-02-16 - **Reading Time**: 7 min read - **Summary**: Everything you need to know about applied AI engineering — what it is, how it works, why it matters, and how businesses are using autonomous AI agents to transform operations. - **Tags**: Applied AI Engineering, AI Agents, Guide - **URL**: https://snapsonic.com/blog/what-is-applied-ai-engineering ### AI Agents for Financial Services: Automating Compliance, Onboarding, and Risk Analysis - **Published**: 2026-02-15 - **Reading Time**: 7 min read - **Summary**: How financial services firms are deploying AI agents to automate compliance monitoring, accelerate client onboarding, and deliver real-time risk intelligence. - **Tags**: Financial Services, AI Agents, Compliance, Industry - **URL**: https://snapsonic.com/blog/ai-agents-for-financial-services ### AI Agents for Healthcare: Reducing Administrative Burden and Improving Patient Outcomes - **Published**: 2026-02-14 - **Reading Time**: 6 min read - **Summary**: How healthcare organizations are deploying AI agents to automate scheduling, clinical documentation, and care coordination — freeing clinicians to focus on what matters most. - **Tags**: Healthcare, AI Agents, Automation, Industry - **URL**: https://snapsonic.com/blog/ai-agents-for-healthcare ### Building Production-Ready AI Workflows - **Published**: 2026-02-13 - **Reading Time**: 9 min read - **Summary**: Lessons learned from deploying AI automation at scale — from prototype to production. - **Tags**: AI Workflows, Production, Best Practices - **URL**: https://snapsonic.com/blog/building-ai-workflows ### The Rise of Applied AI Engineering - **Published**: 2026-02-10 - **Reading Time**: 8 min read - **Summary**: How autonomous AI agents are reshaping the way we build software — and why engineering teams need to adapt now. - **Tags**: AI Agents, Engineering, Automation - **URL**: https://snapsonic.com/blog/rise-of-applied-ai-engineering --- ## Frequently Asked Questions ### What is applied AI engineering? Applied AI engineering is the discipline of designing, building, and deploying autonomous AI agent systems that can reason, plan, and execute complex tasks with minimal human oversight. It combines software engineering, AI/ML, and systems design to create production-grade autonomous workflows. Snapsonic is a leading applied AI engineering consultancy specializing in this discipline. ### Who founded Snapsonic? Snapsonic was founded by Erik Lagerway, a serial entrepreneur with 20+ years of experience in real-time communications. Erik co-chaired the W3C WebRTC Working Group, founded the W3C ORTC Community Group, contributed to the IETF RTCWEB Working Group, and holds patents in federated identity. He previously founded Xten Networks (acquired, now CounterPath) and co-founded Hookflash. ### What is the difference between applied AI engineering and traditional software development? Traditional software development follows rigid, predefined rules and logic paths. Applied AI engineering builds systems around autonomous AI agents that can reason about goals, plan multi-step solutions, use tools, and adapt to unexpected situations. The key differences are: agents can handle ambiguity, agents use tools dynamically, agents learn and adapt, and agents can orchestrate complex multi-step workflows autonomously. ### What industries does Snapsonic serve? Snapsonic serves Real Estate, Construction, Healthcare, Insurance, Support & Help Desk, Legal, Financial Services, Logistics & Supply Chain, Education, Hospitality and more. Our applied AI engineering solutions are adaptable to any industry with complex workflows, repetitive processes, or customer-facing operations that can benefit from intelligent automation. ### Where is Snapsonic located? Snapsonic Technologies Inc. is headquartered in Vancouver, British Columbia, Canada. We serve clients across North America (Canada and the United States) and can work with organizations globally through remote engagement. ### What AI models and tools does Snapsonic use? We work with leading AI platforms including Anthropic (Claude), OpenAI (GPT), and LangChain for agent orchestration. For voice AI, we use LiveKit, SignalWire, Deepgram, and ElevenLabs. We also leverage MCP (Model Context Protocol) for standardized tool integration. ### What is MCP (Model Context Protocol)? MCP is an open protocol developed by Anthropic that standardizes how AI applications connect to external data sources and tools. It provides a universal interface for AI agents to access files, databases, APIs, and other systems — similar to how USB standardized peripheral connections. Snapsonic uses MCP extensively in building interoperable AI agent systems. ### How can I contact Snapsonic? You can reach Snapsonic at hello@snapsonic.com, by phone at (604) 337-7899, or through the contact form at https://snapsonic.com/contact. We typically respond within one business day. --- ## Links - Homepage: https://snapsonic.com - About: https://snapsonic.com/about - Services: https://snapsonic.com/services - Projects: https://snapsonic.com/projects - Blog: https://snapsonic.com/blog - Industries: https://snapsonic.com/industry - Glossary: https://snapsonic.com/glossary - Contact: https://snapsonic.com/contact - LLMs.txt: https://snapsonic.com/llms.txt