AI Automation Built Around Real Workflows
AI automation is the integration of artificial intelligence models—such as LLMs, computer vision, and predictive algorithms—into existing business software to automate complex decisions and data processing.
SOLVEO builds practical AI systems. We focus on integrating AI where it creates measurable system value, from edge inference on embedded devices to massive data processing in the cloud.
What SOLVEO provides
We do not build gimmicky chatbots. We engineer AI integrations that act as intelligent middleware, reducing manual data entry, interpreting unstructured data, and automating decision trees.
- LLM Integrations: Securely connecting enterprise data to Large Language Models using RAG (Retrieval-Augmented Generation) architectures.
- Intelligent Workflows: Automating document processing, data extraction, and customer routing.
- Edge Intelligence: Deploying lightweight models (like TinyML) directly onto microcontrollers for latency-free, offline inference.
- Computer Vision: Automated quality control and object detection for industrial environments.
Typical Architecture (RAG System)
To make an LLM useful for a business, it must have access to private business data securely. We build RAG systems to ensure factual, context-aware AI outputs.
Common Failure Points & Limitations
Hallucinations: LLMs confidently invent facts. We design systems that restrict the LLM to only answer based on retrieved vector context, implementing validation layers before outputting to the user.
Cloud Latency vs Edge AI: Cloud AI APIs have latency. For real-time industrial applications (like detecting a defective part on a conveyor belt), cloud AI is too slow. We pivot these systems to run Edge AI models directly on the hardware.