Natural language processing and Semantic Analysis Powered Intelligence
OAKS SRL · Intelligence & Research
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 8 captures on record
What the publisher says
As described on Microsoft Marketplace.
This application is available only in Italian, English.
What is Semantic Analysis?
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Semantic analysis is an automated process of deriving high-quality information from text.
OAKS SAPI solution
OAKS offers SAPI, a solution based on Azure Machine Learning algorithms to analyze structured and unstructured data.
The solution can be used for analytical purposes like:
- Sentiment analysis(Empathy, Dissatisfaction, Satisfaction categories etc)
- Influencer identification
- User contagion
- Fake news detection
- Web crawler (indexing)
- Summarization (both extraction and abstraction)
- AI-powered chatbot
- Document tagging
- Semantic Categorization
- Keyword, named entities and topics extraction
- Business categorization
- Competitor & Partners identification
Business value of SAPI:
- Saves time and labor costs by automating manual work, minimizing errors
- Ensures services based on analyzing big amount of text data
- Mitigates risks of not receiving crucial correct information at the right time
- Helps making smart decisions on what is fraud, what is risky and what is relevant for business
Use cases:
- Automatic customer request sorting by type, complexity, priority, or profitability, and further passing them on to sales people for immediate actions;
- Improvement of clients satisfaction by immediate detection of pain and gain points and consequent definition of action plan
- Quick acquisition of relevant data from web and databases, to speed up workflows and management;
- Risk management: semantic analysis technology enables complete management of thousands of heterogeneous sources, and provides the ability to link together information and be able to access the right information at the right time;
- Fraud detection through claims investigation: The majority of information in jurisprudence is collected as text. Insurance companies use text mining technologies by combining the results of semantic analysis with structured data to prevent frauds and swiftly process claims.
Preview
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Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
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Publisher resources
2 linksLinked repositories
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