Questions & Answers

AI consulting helps businesses identify where artificial intelligence can drive measurable value - reducing costs, automating processes, or unlocking new revenue streams. A good AI consultant doesn't just recommend tools; they assess your data, workflows, and goals to build a strategy that delivers ROI. At Aviron, we focus on practical, high-impact AI implementations, not theoretical roadmaps.

If you have repeatable processes, data (even unstructured), and at least one area where manual work creates bottlenecks, you're likely ready. You don't need perfect data or a massive budget to start. Our Opportunity Assessment (2-3 weeks) evaluates your readiness and identifies the highest-ROI use cases before any development begins.

Traditional software consulting focuses on building deterministic systems -apps, databases, APIs. AI consulting adds a layer of intelligence: models that learn from data, generate content, make predictions, or automate decisions. Aviron does both. We build the full stack -the AI models and the production software around them -so you get a complete, deployable solution, not just a proof of concept.

We define success metrics before writing a single line of code. Common metrics include: time saved per process, cost reduction percentage, revenue increase, error rate reduction, and customer satisfaction improvements. For example, one of our clients saw a 28.8% revenue increase and 500% growth in search traffic after our engagement. We track KPIs throughout every project phase.

We've delivered AI solutions across manufacturing, healthcare, e-commerce, SaaS, facilities management, education, and energy. Our sweet spot is established businesses ($10M+ revenue) with clear processes to optimize. The specific industry matters less than having real data and real problems to solve.

AI agents are autonomous software systems that can perform complex tasks, make decisions, and interact with other systems on your behalf. Unlike simple chatbots, agents can chain multiple actions together -searching databases, calling APIs, generating reports, and taking action based on the results. We build custom AI agents for use cases like customer service automation, internal knowledge retrieval, manufacturing floor assistance, and CRM intelligence.

RAG combines the power of large language models (like GPT or Claude) with your company's proprietary data. Instead of relying solely on the model's training data, RAG retrieves relevant information from your documents, databases, or knowledge bases and uses it to generate accurate, context-specific answers. This dramatically reduces hallucinations and makes AI responses trustworthy for business-critical applications. We build production-grade RAG pipelines with ingestion, tuning, evaluation, and observability built in.

Yes. We specialize in integrating AI agents with existing platforms -CRMs, ERPs, internal tools, databases, and third-party APIs. Our agents are built to work within your current tech stack, not replace it. We've integrated with manufacturing systems, healthcare platforms, work order management tools, and custom SaaS products.

We use multiple strategies: retrieval-augmented generation (grounding responses in your actual data), evaluation frameworks to measure accuracy, guardrails to prevent hallucination, human-in-the-loop review for critical decisions, and continuous monitoring in production. We also fine-tune models on domain-specific data when needed for maximum accuracy.

We follow a proven 3-step process: (1) Opportunity Assessment (2-3 weeks) -we audit your business processes, analyze AI feasibility, and deliver a roadmap with ROI projections. (2) Pilot Sprint (4-6 weeks) -we build and deploy an MVP that proves value. (3) Co-Build Retainer (ongoing) -we become your dedicated AI development team, scaling solutions and upskilling your staff. You can start with just the assessment -there's no long-term commitment required upfront.

Our first Pilot Sprint typically ships a working MVP in 4-6 weeks. The Opportunity Assessment before that takes 2-3 weeks. So from first conversation to working AI in production, you're looking at roughly 6-9 weeks. We move fast because we've built this type of system before and have established patterns for common use cases.

Our 60-minute strategy call covers three things: (1) an AI opportunity assessment specific to your business, (2) realistic ROI projections and timeline estimates, and (3) a clear next-steps roadmap -whether you work with us or build internally. No sales pressure, no generic pitch. We discuss your actual challenges and give you actionable insights.

We're based in St. Louis, MO with a distributed team across the U.S. We primarily serve U.S.-based companies, but we've worked with international organizations and are open to engagements worldwide. All communication and collaboration happens remotely.

We primarily work with established businesses generating $10M+ in annual revenue. These companies typically have defined processes, existing data, and clear business problems where AI can deliver meaningful ROI. That said, we've also worked with funded startups that have strong technical foundations and ambitious product roadmaps.

Three things set us apart: (1) We build and deploy -we're not a strategy-only firm. We write the code, ship to production, and support it. (2) Speed -our pilot sprints deliver working solutions in 4-6 weeks, not months. (3) Full-stack capability -we handle the AI layer (RAG, agents, fine-tuning) and the application layer (.NET, React, Azure) so you don't need multiple vendors. Our team has 70+ years of combined experience and includes Microsoft MVPs.

Our core stack includes: AI/ML -OpenAI, Anthropic Claude, Azure AI, open-source models, LangChain, and custom RAG pipelines. Frontend -React, Next.js, React Native, Astro. Backend -.NET, ASP.NET Core, Node.js. Cloud -Microsoft Azure, Azure DevOps. We select technologies based on your requirements, existing infrastructure, and long-term maintainability -not trends.

Yes. We integrate AI capabilities into existing systems rather than requiring you to rebuild from scratch. Whether you're running .NET, Node.js, Python, or legacy systems, we can connect AI solutions through APIs, microservices, or embedded models. Our team has deep experience with enterprise integrations across diverse technology environments.

Both, depending on your needs. For most business applications, we use foundation models (GPT-4, Claude, open-source LLMs) with techniques like RAG and fine-tuning to customize them for your domain. For specialized use cases -predictive analytics, IoT classification, computer vision -we build custom ML models trained on your data. We always choose the approach that delivers the best results for the lowest cost.

We take data security seriously. We can deploy models within your Azure tenant so data never leaves your environment. We implement role-based access controls, data encryption at rest and in transit, and audit logging. For regulated industries (healthcare, finance), we ensure compliance with relevant standards. We're happy to work within your security team's requirements and sign NDAs before any engagement.

Yes. We offer two types of training: (1) AI coding workflow training for engineers -teaching your developers to use AI tools effectively in their daily work. (2) Professional productivity training for knowledge workers -helping your broader team use tools like Copilot, ChatGPT, and other AI assistants to work more efficiently. We also do knowledge transfer throughout every engagement so your team can maintain and extend what we build.

Voice AI enables natural, spoken interactions between users and your software systems. This includes voice-enabled customer service agents, interactive voice response (IVR) replacements, voice-controlled internal tools, and conversational interfaces for hands-free environments like manufacturing floors. We build voice solutions that understand context, handle interruptions, and deliver human-like interaction quality.