What we do
Predictive models
Get the power of ChatGPT without sending your data to the cloud. We deploy large language models directly on your servers—fully private, compliance-ready, and built for regulated industries.
Private LLM deployments
Custom chatbots (on-prem)
We transform messy, unlabeled datasets into clean, annotated training data ready for production. From image labeling to text classification and 3D annotation—we handle the tedious work so your models perform better.
Image & Video Annotation
Our computer vision solutions automate quality control, track objects, read documents, and spot anomalies faster than any human can. If you need AI that can see, we build it.
Object detection & tracking
Image classification
Quality control automation
Video analytics
OCR & document processing
We identify where AI can actually help your business—cutting costs, automating workflows, improving decisions. Then we build and deploy the solutions that make it happen. Business effectiveness and process optimization with AI.
Process Automation
Performance Analytics
Decision Intelligence
About SURG Solutions
We founded SURG Solutions with one goal, to use AI and data to solve real problems, save money and time. Our first project came almost by chance, but it turned into exactly what the client needed. That one project grew into several and we’re proud to still work with them today.
Being at the start is our strength. As two founders we are involved in every project and because we’re a small company every client gets our full attention. Each project is a partnership we want to make perfect.
From day one we brought together top people in AI, machine learning and data strategy. This way we combine curiosity with the latest technology and expert know-how. Whether it’s secure on-prem LLMs, automation pipelines or custom AI systems, we deliver solutions that are innovative, practical and bring measurable impact.
Case studies
Case 1
Database Intelligence Chatbot
Challenge:
The company needed a secure and scalable solution to interact with their internal database containing massive datasets (5,000+ rows, 10,000+ columns). Manual data analysis and retrieval was time-consuming and required technical expertise, creating bottlenecks in decision-making processes.
What We Built:
Natural Language Querying (AI-powered): We developed an intelligent chatbot that translates natural language questions into complex database queries, allowing non-technical users to extract insights instantly without SQL knowledge.
Advanced Analytics Engine: The system performs real-time counting, filtering, aggregation, and trend analysis across massive datasets, delivering results in seconds rather than hours.
Secure Local Architecture: Built with enterprise-grade security protocols running entirely on local infrastructure, ensuring complete data privacy with no external data transmission. The system maintains role-based permissions and audit trails while keeping all sensitive information within the company's network.
Thanks to AI-powered natural language processing with robust database querying, we dramatically reduced analysis time and eliminated manual data processing. The system empowers teams to make data-driven decisions faster, reduces dependency on technical staff, and ensures instant access to critical insights at all times.
Local LLM
Vector Databases
Case 2
Robotic Warehouse Optimization
Challenge:
A fully automated robotic warehouse needed a smarter backend system to significantly speed up product dispensing and improve how items are placed throughout the storage system. The new logic had to follow strict operational rules while also learning from real demand patterns, predicting seasonality, and adapting product placement to ensure maximum efficiency using machine learning.
What We Built:
Stock-In Optimization (ML-powered): We developed a system that uses machine learning scoring to predict the demand for each product. Based on this prediction, the system calculates optimal storage locations to ensure high-demand products are stored in the fastest-access spots, ready for fast dispensing.
Fast Dispensing: The system ensures FEFO (First Expiry First Out) compliance, handles multi-product orders, and balances robot tasks efficiently to avoid collisions and maximize throughput.
Nightly Reorganization: Based on demand predictions, the system repositions products dynamically to keep high-demand items easily accessible.
By integrating machine learning–based demand prediction with automated stock-in logic, fast dispensing workflows, and nightly warehouse optimization, we significantly increased the speed and efficiency of product dispensing. The system continuously adapts storage placement, minimizes handling time, and ensures high-demand items are always positioned for the fastest possible output.
FastAPI
Machine Learning
Case 3
Churn Predictor Model
A fast-growing subscription app struggled with rising monthly churn and had no clear way to identify users who were about to cancel. We designed and delivered an AI-powered churn prediction system that helped them take action before users left.
What We Did:
Analyzed user behavioral data (logins, usage, features, tickets, payments) to uncover hidden churn patterns.
Identified which subscribers were most likely to churn, including risk scores for every user segment.
Added explainability tools to show key churn drivers
Delivered a simple web app for single or batch predictions with retention recommendations.
Outcome
Within the first month, the company started identifying most high-risk users early and reduced churn by 22%, protecting a significant portion of recurring revenue. This gave them a clear retention strategy and a strong competitive advantage.
Machine Learning
Data Analysis
Prediction Model
Case 4
Automating Open-Ended Response Analysis
Challenge:
A survey and analytics provider struggled with large volumes of open-ended responses that had to be manually categorized, taking up to 8 hours per week per analyst and slowing down the process.
Solution:
We developed an automated open-ended response analysis system using machine learning and text analysis to quickly extract and categorize responses. The tool analyzes thousands of texts in real time and assigns them to relevant categories.
Outcome:
The company saved 3-8 hours per analysis, significantly speeding up the process and enabling faster decision-making and better client offerings. The service will be soon available on www.recodeq.com
Natural Language Processing
Clients
