AI & Machine Learning Development Services
AI and machine learning development is the practice of building software that learns from data to predict, classify, generate, or perceive. AutoNex Solution designs and ships custom AI - LLM applications, computer vision, NLP, and predictive analytics - translated into measurable business outcomes, with 90%+ production accuracy and full code ownership.
What is custom AI/ML development?
Custom AI/ML development means building models and the software around them for your specific problem and data, instead of bolting on a generic API. It spans four families: large language model (LLM) applications that read, write, and reason over text; computer vision that interprets images and video; natural language processing (NLP) that extracts meaning from documents and speech; and predictive analytics that forecasts outcomes like churn, demand, or fraud. The hard part isn't the model - it's the data pipeline, evaluation, and deployment that make it reliable in production. That's what we own.
Where machine learning pays off fastest
Four high-ROI applications we ship into production.
LLM applications & RAG
Copilots, document Q&A, summarisation, and agents grounded in your data - built on GPT-5, Claude, or open-source models.
Computer vision
OCR, image recognition, defect detection, and video analytics that turn pixels into structured, actionable data.
Predictive analytics
Churn, demand forecasting, fraud, and lead scoring models that put a number on what happens next.
NLP & document AI
Extraction from complex PDFs and forms, classification, sentiment, and entity recognition at scale.
How we deliver an AI/ML project
From a fuzzy idea to a measured model running in your cloud.
Discovery & feasibility
We define the prediction, the success metric, and whether the data can actually support it - before you spend.
Data & baseline
Pipeline the data, label what's needed, and stand up a baseline model to prove the signal is real.
Model & evaluation
Iterate to target accuracy with rigorous offline evaluation, then validate against live edge cases.
Deploy & monitor
Ship behind an API in your cloud, with monitoring for drift, latency, and accuracy in production.
Discovery & feasibility
We define the prediction, the success metric, and whether the data can actually support it - before you spend.
Data & baseline
Pipeline the data, label what's needed, and stand up a baseline model to prove the signal is real.
Model & evaluation
Iterate to target accuracy with rigorous offline evaluation, then validate against live edge cases.
Deploy & monitor
Ship behind an API in your cloud, with monitoring for drift, latency, and accuracy in production.
The AI/ML stack we build on
Everything, delivered and owned by you.
No lock-in, no hostage code. On delivery you get the full source, deployed in your cloud, with a 30-day post-launch window of free iteration.
Start your project- Production model hitting an agreed accuracy target
- Reproducible data & training pipeline
- Model served behind a clean API in your cloud
- Offline + live evaluation reports
- Monitoring for drift, latency & accuracy
- Full source code, weights, and documentation
Related work we've shipped
Pixara AI
Sophisticated AI platform converting text prompts into fully edited videos.
Sentiment Analysis
Logistic regression models to classify the sentiment of movie reviews.
Audio Classification
A machine learning model to process and classify audio signals using Neural Networks.
AI & Machine Learning Development FAQs
We agree a target accuracy upfront during the feasibility phase and won't ship below it. Across production projects we typically reach 90%+ on the agreed metric - but the honest answer depends on your data quality, which we assess in the first three days before you commit.