Turn generative AI into practical, production-ready solutions. From custom AI copilots and content generation platforms to RAG systems and enterprise LLM integrations, Austronix helps you build generative AI applications that are useful, secure and scalable.
Generative AI can create text, code, images, documents and conversations — but turning those capabilities into dependable business software requires engineering, not just model access. Austronix designs and builds generative AI applications around your workflows, data, users and business objectives.
Generative AI strategy and consulting
Custom LLM application development
AI copilot development
AI content generation systems
RAG and knowledge-grounded AI
Prompt engineering and optimization
Multimodal AI applications
AI API and model integration
AI safety and guardrails
Fine-tuning and model adaptation
Cloud generative AI deployment
Generative AI monitoring and optimization
Identify practical generative AI opportunities, evaluate use cases and define a technical roadmap aligned with business goals.
Build complete applications powered by large language models, designed around your workflows, users and business rules.
Develop AI copilots that assist teams and customers inside your applications with context-aware suggestions and actions.
Build systems that generate, transform and manage text, documents, marketing content and structured business content.
Connect generative AI with your business documents and data sources so responses are grounded in accurate, relevant information.
Design, test and optimize prompts to improve reliability, accuracy, tone and cost-efficiency of generative AI applications.
Build applications that understand and generate across text, images, audio and documents using modern multimodal models.
Adapt generative AI models to your domain, language and business requirements through fine-tuning and evaluation.
Integrate generative AI models and services with existing applications, APIs, databases and enterprise systems.
Implement controls that keep generative AI outputs safe, compliant and aligned with your business policies.
Deploy generative AI applications on secure and scalable cloud infrastructure with proper monitoring and cost controls.
Continuously improve generative AI systems through monitoring, evaluation, prompt tuning and model updates.
Generative AI helps teams draft, transform and publish content in a fraction of the time required by manual workflows.
Grounding generative AI in business documents lets teams find accurate answers in seconds instead of searching manually.
Automating drafting, summarizing, routing and information processing frees teams to focus on higher-value work.
We empower organizations across diverse sectors with custom technology architectures designed to solve unique operational challenges and accelerate market growth.
We create secure and scalable digital solutions for healthcare providers, pharmaceutical organizations, biotechnology companies, and medical technology businesses.
Healthcare platforms, patient portals, hospital systems, and digital health applications.
Research platforms, pharmaceutical operations, data management, and biotechnology solutions.
Connected medical technology, device platforms, monitoring systems, and digital medical solutions.
We understand your business objectives, users, data sources, workflows and the outcomes you want generative AI to deliver.
We identify suitable generative AI use cases, define requirements and select appropriate models, APIs and architecture based on cost, quality and privacy needs.
We design prompt architectures, retrieval systems, data pipelines and application architecture needed to ground and control generative AI outputs.
Where required, we prepare business documents, structured data and knowledge sources for embedding, retrieval and generative AI integration.
Our engineers build the generative AI application using appropriate models, frameworks, retrieval systems, backend services and software engineering practices.
We evaluate output quality, relevance, tone, safety, latency and cost, and validate guardrails, PII handling and edge-case behavior.
We deploy the generative AI solution to production with secure infrastructure, monitoring, logging and cost controls.
We monitor output quality, usage, latency, errors and cost to identify issues, regressions and optimization opportunities.
After launch, we improve prompts, retrieval, workflows, model choices and application behavior as business needs and AI capabilities evolve.
We engineer generative AI systems for reliability, grounding, safety and cost — so they hold up in real business environments, not just demos.
We connect generative AI to your documents, databases and knowledge sources so responses are accurate, relevant and traceable.
We choose the right models and architecture for your use case — commercial APIs, open-source models or a hybrid approach — based on quality, cost and privacy.
Guardrails, PII handling, moderation, prompt-injection defenses and audit logging are built into the architecture from the start.
Caching, routing, prompt optimization and monitoring keep generative AI costs predictable as usage scales.
We continue supporting your platform with prompt tuning, model updates, evaluation, new capabilities and maintenance after launch.
Generative AI solutions are software applications and systems built on large language models and other generative models that can create text, images, code, audio and structured content — integrated into real business workflows to solve specific problems.
We build AI copilots, enterprise knowledge assistants, content generation platforms, RAG applications, document intelligence systems, conversational AI applications, multimodal applications, AI-powered SaaS products and custom LLM applications.
We work with a range of models including OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock and open-source models such as Llama and Mistral. Model choice depends on quality, cost, privacy and use-case requirements.
Retrieval-Augmented Generation (RAG) connects a generative AI model to your business documents and data sources so it retrieves relevant context before generating a response. This reduces hallucinations and makes outputs grounded, accurate and traceable to sources.
Yes. We build knowledge-grounded applications using approved business documents, knowledge bases and internal data — with appropriate access controls, retrieval pipelines and grounding techniques.
We use retrieval grounding, prompt engineering, output validation, guardrails, evaluation frameworks and continuous monitoring to reduce hallucinations and keep outputs aligned with business requirements.
Yes. Existing websites, SaaS platforms, internal tools and business applications can be enhanced with generative AI features such as copilots, assistants, summarization, content generation and workflow automation.
We apply secure authentication, role-based access control, API key protection, PII detection, content moderation, prompt-injection defenses, audit logging and infrastructure hardening. Controls are tailored to your requirements and risk profile.
We use caching, model routing, prompt optimization, streaming, batching, usage monitoring and cost alerts to keep generative AI costs predictable as usage grows.
A focused proof of concept can typically be delivered in 2–4 weeks. A production generative AI application with retrieval, guardrails and integrations usually takes 8–16 weeks, depending on scope. We work in short iterations so you see progress early.
Yes. We provide ongoing monitoring, evaluation, prompt tuning, model and API updates, retrieval improvements, guardrail updates, cost optimization and new feature development after launch.
Yes. We can fine-tune or adapt models using your domain data where it improves quality, tone or task-specific accuracy — with proper evaluation and version management.
