We build production AI systems — not demos. AppliconSoft designs, ships, and operates AI agents, LLM-powered product features, and automation pipelines that hold up under real users, real data, and real accountability.
Our AI work covers: AI agents that execute multi-step workflows with human-in-the-loop controls; LLM integration (OpenAI, Anthropic, and open-weight models) into your existing product; retrieval-augmented generation (RAG) over your documents and data; evaluation frameworks so quality is measured before and after every change; and observability so you always know what your AI did and why.
We don’t just build AI for clients — we ship our own. ChatCactus, TrackPilot AI, SocialRocket AI, TeamSuite AI, and FlowLedger Pro were designed, built, and are operated by this team. That’s how we know what breaks in production — and how to build systems that don’t.
Every engagement starts with your data, your workflow, and the decision you want to automate. We define success metrics up front, build evals before we build features, and integrate into your stack — not the other way around.
Python, TypeScript, OpenAI & Anthropic APIs, LangChain / LlamaIndex, vector databases (pgvector, Pinecone, Qdrant), PostgreSQL, MySQL, AWS & Google Cloud, Docker, CI/CD, model evaluation & LLM observability tooling.
We deliver data processing workflows, predictive models, intelligent applications, automation systems, reporting dashboards and AI-supported features. Our approach starts with business objectives and data readiness, then moves through cleaning, modeling, validation, integration and continuous improvement.
Frequently Asked Questions
AppliconSoft designs, builds, and operates production-grade AI systems, including multi-step workflow AI agents with human-in-the-loop controls, LLM product integrations, retrieval-augmented generation (RAG) pipelines, continuous evaluation frameworks, and system observability.
AppliconSoft integrates both proprietary foundation models (OpenAI, Anthropic APIs) and open-weight models directly into existing client software stacks, custom-building RAG architectures, vector search layers, and automated data pipelines.
- Languages: Python, TypeScript
- Frameworks: LangChain, LlamaIndex
- Databases & Vector Stores: PostgreSQL, MySQL, pgvector, Pinecone, Qdrant
- Infrastructure & Cloud: AWS, Google Cloud, Docker, CI/CD pipelines
- LLM Tooling: Model evaluation and LLM observability frameworks
Deliverables include custom AI agents, automated data processing workflows, predictive machine learning models, reporting dashboards, vectorized retrieval systems, and integrated smart features within existing products.
AppliconSoft sets up strict, custom evaluation frameworks (evals) before building features, ensuring accuracy is quantified before and after every release. They also implement full LLM observability to trace every output, decision, and system action.
AppliconSoft operates its own suite of production AI software, including ChatCactus, TrackPilot AI, SocialRocket AI, TeamSuite AI, and FlowLedger Pro.
How does an AI development project begin with AppliconSoft?
No. AppliconSoft integrates custom AI solutions directly into your existing infrastructure, codebase, and cloud environments.
Book a 30-minute AI architecture call.
We'll map your first agent use case, estimate honestly, and tell you plainly if AI is the wrong tool for the job.
