Practical AI Solutions for Your Business
Statnetics builds AI that solves specific business problems, from text analytics and intelligent matching to LLM-powered automation, and integrates it into the products and workflows you already use.
- Start from a measurable business problem
- Prove value with a small proof of concept
- Integrate into your existing systems
- Test and monitor outputs for quality
- Keep sensitive data protected
Where AI adds value
Text analytics
Classify, summarize and extract insight from notes, documents, feedback and opinions.
Intelligent matching
Rank and match candidates, products or records against requirements.
LLM automation & RAG
Assistants and workflows grounded in your own documents and data.
AI in quality engineering
AI-assisted test case generation and failure analysis, as used in CloudQA.
Examples of our AI work
AI-powered job matching for HR freelancers
A matching system that filters resumes and professional profiles to surface the most qualified candidates for senior management and CXO roles, so recruiters spend their time on the best fits.
- Resume and profile parsing
- Requirement-based ranking
- Shortlists recruiters can review
Text analytics for solar project bids
Text analytics that extracts insight from meeting notes and public opinions about proposed solar projects, so bid teams understand community sentiment and the factors that matter.
- Text classification
- Sentiment and theme analysis
- Inputs for bid strategy
From idea to production
- DefinePick a use case with clear value and success measures.
- PrototypeA small proof of concept on real data to test accuracy and value.
- IntegrateBuild it into your product or workflow, with security and access controls.
- EvaluateTest outputs, monitor quality and improve over time.
AI solutions questions
What kind of AI projects does Statnetics take on?
Practical, business-focused AI: text analytics and classification, matching and ranking, document and data extraction, and LLM-powered automation with retrieval-augmented generation (RAG), integrated into your existing systems.
Do we need our own data science team?
No. We handle data preparation, model selection, integration and testing, and work with your product and engineering teams on requirements and rollout.
Which AI models do you use?
We choose per project, including OpenAI models via API and other providers, and design solutions so you are not locked into one model.
How do you handle our data?
We use your data only for your project, follow the access controls you set, and can design solutions that keep sensitive data out of third-party models.
How do we start?
Request a consultation. We will discuss your use case and suggest a small proof of concept to test value before a larger build.
Have an AI use case in mind?
Tell us the problem you want to solve. We will suggest a practical approach and a small first step.