{"id":16359,"date":"2026-07-02T13:22:53","date_gmt":"2026-07-02T06:22:53","guid":{"rendered":"https:\/\/aigencorp.com\/?page_id=16359"},"modified":"2026-08-03T13:22:59","modified_gmt":"2026-08-03T06:22:59","slug":"data-intelligence","status":"publish","type":"page","link":"https:\/\/aigencorp.com\/en\/data-intelligence\/","title":{"rendered":"Data Intelligence"},"content":{"rendered":"\n
\n
<\/div>\n\n\n
\n
\"\"<\/figure><\/div>\n\n\n
<\/div>\n\n\n\n
\n\n
\n

Business Decision Predictive Models<\/h3>\n\n

\n\nCase Study\n<\/strong>\n<\/h3>\n\n \nClaim Triage & Straight-Through Processing\n \n <\/a>\n\n \n Audit Enablement\n <\/a>\n <\/div>\n\n
<\/div>\n\n
\n

Medical Encoding & Anomaly Detection<\/h3>\n\n \n AIGEN Medical Encoding Flow\n <\/a>\n\n

Case Study<\/strong><\/h3>\n\n \n Medical Cost Intelligence\n <\/a>\n\n \n Medical Anomaly Detection\n <\/a>\n <\/div>\n\n
<\/div>\n\n
\n

Product Recommendation Engines<\/h3>\n\n

Case Study<\/strong><\/h3>\n\n \n SKU-Level Product Recommendation\n <\/a>\n\n \n Customer Lifetime Value\n <\/a>\n\n \n Inventory & Demand Forecasting\n <\/a>\n <\/div>\n\n
<\/div>\n
\n

Sales Uplift with Next Best Offer and Next Best Channel Prediction by AI<\/h3>\n\n

Case Study<\/strong><\/h3>\n\n \n Insurance Company NBO\/NBC Deployment\n <\/a>\n\n \n <\/div>\n\n<\/div>\n<\/div><\/div><\/div>\n\n\n\n
\n

<\/span><\/span>Your Data,<\/h1>\n\n\n\n

<\/span><\/span>Transformed Into Decisions<\/h1>\n\n\n\n

<\/span><\/span>In every dataset lies a competitive advantage waiting to be unlocked. AIGEN builds the AI infrastructure that turns raw business data into predictive power \u2014 cutting fraud, reducing waste, and growing revenue for Thailand’s most forward-looking enterprises.<\/p>\n\n\n\n

<\/div>\n\n\n\n
\n\n
\n
\n
\n
\n
<\/div> \n
<\/div> \n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
\n
<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

\n Predict What Happens Next\n <\/h3>\n

\nLeverage historical data to accurately forecast outcomes, such as claim approvals or customer churn, transitioning decision-making from reactive to proactive.\n <\/p>\n <\/article>\n\n

\n
\n \n
\n\n
\n \n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div> \n
<\/div>\n \n
<\/div> \n \n
<\/div> \n
<\/div> \n
<\/div> \n
<\/div> \n
<\/div> \n
<\/div> \n
<\/div> \n
<\/div> \n \n
<\/div> \n \n
<\/div> \n <\/div> \n\n\n <\/div> \n\n <\/div>\n

\n Surface Hidden Risk\n <\/h3>\n

\nAI systematically flags anomalies and fraud patterns that human reviewers might miss. Catch more frauds and leakages. Go through at speed. Audit 100% of cases.\n <\/p>\n <\/article>\n\n

\n
\n \n
\n\n
\n
\n
<\/div> \n <\/div> \n
\n
<\/div> \n
<\/div>\n <\/div> \n
\n
<\/div> \n
<\/div> \n
<\/div>\n <\/div> \n
\n
<\/div> \n
<\/div> \n
<\/div>\n
<\/div> \n <\/div> \n
\n
<\/div> \n
<\/div> \n
<\/div>\n
<\/div> \n
<\/div> \n <\/div> \n <\/div> \n\n <\/div> \n\n\n\n\n\n <\/div>\n

\nUnlock Granular Insight\n <\/h3>\n

\nGaining granular visibility into SKU margins and hospital charging patterns, enabling better product design and vendor negotiations.\n <\/p>\n <\/article>\n\n

\n
\n\n\n\n
\n \n \n \n \n \n \n \n \n <\/g> \n <\/svg> \n <\/div>\n\n\n\n \n <\/div>\n

\n Accelerate Decisions\n <\/h3>\n

\n Reduce decision cycles from days to seconds. Straight-through processing for routine cases frees human expertise for the complex judgments that truly need it.\n <\/p>\n <\/article>\n\n

\n
\n\n\n\n
\n \n
\n
<\/div> \n
<\/div>\n
<\/div> \n
<\/div>\n
<\/div> \n <\/div> \n <\/div>\n\n\n\n \n <\/div>\n

\nGrow Revenue Intelligently\n <\/h3>\n

\nRecommend intelligently. Forecast demand in real-time. Transform daily operations into revenue by delivering the right products to the right customers instantly.\n <\/p>\n <\/article>\n\n

\n
\n \n\n\n
\n \n
\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n
<\/div>\n <\/div>\n <\/div>\n\n\n\n\n\n <\/div>\n

\nBuild Compounding Advantage\n <\/h3>\n

\nCompound the value with more data. Organizations investing early in structured data and intelligent systems secure a growing, long-term competitive lead.\n <\/p>\n <\/article>\n\n<\/section>\n<\/div><\/div><\/div>\n\n\n\n

\n

<\/span><\/span>Business Decision Predictive Models<\/h2>\n\n\n\n

<\/span><\/span>AIGEN creates custom machine learning models using your historical data to automate high-stakes business judgments like claim approvals, credit extensions, and fraud detection. These models deliver faster, more consistent, and highly accurate decisions at scale, far surpassing manual processes.<\/p>\n\n\n\n

<\/div>\n\n\n\n
\n\n
\n \"\"\n\n

\n Insurance Claim
\n Outcome Prediction\n <\/h3>\n\n \n\n

\n Predict approval, rejection, or investigation priority before a claim enters the manual queue – triaging workflows and accelerating straight-through processing.\n <\/p>\n <\/article>\n\n

\n \"\"\n\n

\n Fraud Detection
\n & Scoring\n <\/h3>\n\n \n

\n Multi-variable fraud scoring across claim history, provider patterns, diagnosis codes, and behavioural signals \u2014 surfacing suspicious cases human reviewers miss.\n <\/p>\n <\/article>\n\n

\n \"\"\n\n

\n Credit Decision Support\n <\/h3>\n\n \n\n

\n Augment credit underwriting with AI risk scores derived from transactional, behavioural, and external data – reducing defaults while expanding approval rates for creditworthy customers.\n <\/p>\n <\/article>\n\n

\n \"\"\n\n

\n Audit & Compliance
\n Screening\n <\/h3>\n\n \n\n

\n AI-powered audit trails that process transaction volumes no human team could review \u2014 identifying exceptions, policy breaches, and anomalies across your entire book of business.\n <\/p>\n <\/article>\n\n<\/section>\n<\/div><\/div><\/div>\n\n\n\n

\n
\n\n

Case Study<\/h2>\n\n \n\n
\n\n

\n Insurance Fraud Detection\n <\/h3>\n\n

\n Catching Fraud at a Scale No Team Could Match\n <\/p>\n\n \"\"\n\n

\nA leading Thai insurer struggled with post-payment losses from high-volume fraudulent accident claims that overwhelmed human reviewers. AIGEN developed a fraud prediction model trained on years of historical data to identify suspicious patterns. The model now scores every claim before adjudication, triaging high-risk cases for specialist review while enabling straight-through processing for clean claims.\n <\/p>\n\n <\/div>\n\n \n\n

\n\n

\n Claim Triage & Straight-Through Processing\n <\/h3>\n\n

\n Screening Claims So Humans Focus on What Matters\n <\/p>\n\n \"\"\n\n

\n Facing days of backlog from thousands of weekly submissions that will only keep growing with business, a leading insurer implemented AIGEN’s claim decision support system. \nThe solution automates classification by risk and complexity, selects policy eligibility, and predicts outcomes, all with explanation. This achieved a dramatic reduction in handling time and a significant uplift in adjuster productivity, focusing human expertise on the most complex cases.\n <\/p>\n\n <\/div>\n\n \n\n

\n\n

\n Audit Enablement\n <\/h3>\n\n

\n Auditing What Was Previously Impossible to Audit\n <\/p>\n\n \"\"\n\n

\nCompliance teams of a motor insurance company previously sampled only 5\u201310% of transactions due to human limits. AIGEN’s automated audit model now screens 100% of transactions against policy rules and anomalies, turning sampling into a comprehensive control.\n <\/p>\n

\nIn another case, an insurer using third-party administrators (TPAs) as claim processor can now move beyond merely random reviews of high-value claims. AIGEN\u2019s aiClaim streamlines checks, allowing more cases to be audited to catch leakages and mistakes, maximizing savings.\n <\/p>\n\n <\/div>\n\n<\/section>\n<\/div><\/div><\/div>\n\n\n\n

\n
\n\n\n\n
<\/div>\n\n\n\n
\n\n
\n

AI Consultation Services<\/h3>\n\n
\n Our AI experts are here to guide you.\n <\/div>\n\n

\n We provide tailored AI recommendations, hands-on demonstrations,\n and strategic consulting to design solutions that fit your business\n needs perfectly.\n <\/p>\n\n \n Consult with experts\n <\/a>\n <\/div>\n\n

\n

Partner with AIGEN<\/h3>\n\n
\n for Smarter Business Growth\n <\/div>\n\n

\n Join us in shaping the future of business with AI.\n We help integrate advanced technologies into your\n business strategy unlocking sustainable competitive advantages.\n <\/p>\n\n \n Learn more\n <\/a>\n <\/div>\n\n<\/section>\n\n\n\n

<\/div>\n\n\n\n
\n<\/div><\/div><\/div>\n\n\n\n
\n
\n

Medical Encoding & Anomaly Detection<\/h2>\n<\/div><\/div><\/div>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\n

<\/span><\/span>Hospital invoices are highly unstructured and inconsistent. A single item, like paracetamol, can appear under numerous names and abbreviations across various billing systems, making analysis difficult without normalization. AIGEN’s Medical Encoding engine addresses this by mapping diverse Thai healthcare line items into standardized categories. This converts fragmented invoice data intostructured intelligence that enables deep cost insights and effective anomaly detection.<\/p>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n

\n
<\/div>\n\n\n\n

<\/span><\/span>AIGEN Medical Encoding Flow<\/h2>\n\n\n\n
\"\"<\/figure>\n<\/div><\/div><\/div>\n\n\n\n
\n
\n\n

Case Study<\/h2>\n\n \n
\n\n

\n Medical Cost Intelligence\n <\/h3>\n\n

\n From Invoice Chaos to Category-Level Cost Insight\n <\/p>\n\n

\n \"\"\n <\/div>\n\n

\nA health insurer was paying out billions of baht in medical claims annually with almost no visibility into what they were actually paying for at a granular level. AIGEN encoded and categorised all medical line items from thousands of hospital invoices \u2014 standardising drug names, medical procedures, and consumables into a clean taxonomy. For the first time, the insurer could see exactly how much each brand of paracetamol cost at each hospital across their network \u2014 benchmarking prices, identifying outliers, and entering provider negotiations with data-backed confidence.\n <\/p>\n\n <\/div>\n\n \n

\n\n

\n Medical Anomaly Detection\n <\/h3>\n\n

\n Detecting Irrelevant Medicines That Drain Millions\n <\/p>\n\n

\n
\n \"\"\n <\/div>\n <\/div>\n\n

\n Medicines prescribed for conditions unrelated to a patient’s primary diagnosis are a significant sourceof claim leakage \u2014 whether from fraud, clinical waste, or billing abuse. AIGEN’s anomaly detection model cross-references every medicine line item against the diagnosis and treatment context, automatically flagging items that cannot be clinically justified. Cases that would take a medical reviewer hours to detect \u2014 across thousands of claims per week \u2014 are surfaced in seconds, protecting insurers from losses that human teams simply don’t have the bandwidth to catch.\n <\/p>\n\n <\/div>\n\n<\/section>\n<\/div><\/div><\/div>\n\n\n\n

\n
\n

<\/span><\/span>Product Recommendation Engines<\/h2>\n<\/div><\/div><\/div>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\n

<\/span><\/span>Each customer interaction is a chance to offer the right product at the perfect time. AI-personalized recommendations drive buying behavior far better than generic catalogues. AIGEN develops recommendation engines that analyze customers, geographical localization, unstructured sales intelligence, inventory, and market trends to significantly boost conversion rates and lifetime value.<\/p>\n<\/div><\/div><\/div>\n\n\n\n

\n
\n\n

Case Study<\/h2>\n\n \n
\n\n

\n SKU-Level Product Recommendation\n <\/h3>\n\n

\n Turning Customer Data into Targeted Sales Opportunities\n <\/p>\n\n \"SKU-Level\n\n

\nA distribution business with thousands of active SKUs was unable to effectively guide its sales team or digital storefront toward the most relevant products for each customer. \nAIGEN can create a multi-factor recommendation model incorporating geographical proximity (regional product preferences), purchasing cadence and history, customer segment profiles, and current inventory levels, among other factors.\n <\/p>\n

\nSales teams can now spend less time browsing catalogues and more time closing, while deal basket sizes grew as customers engaged with relevant product suggestions rather than generic category lists.\n <\/p>\n\n <\/div>\n\n \n

\n\n

\n Customer Lifetime Value\n <\/h3>\n\n

\n From One-Time Buyers to Loyal, High-Value Customers\n <\/p>\n\n \"Customer\n\n

\nAI-driven, timely recommendations strengthen the business-customer bond. By matching products to genuine needs, the engine encourages more frequent returns and broader purchases. This significantly increases customer lifetime value, transforming the recommendation system into a driver for sustained revenue growth.\n <\/p>\n\n <\/div>\n\n<\/section>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n

\n
\n
<\/div>\n\n\n\n

Inventory & Demand Forecasting<\/h2>\n\n\n\n

<\/span><\/span>Over-ordering ties up capital and fills warehouses with obsolete stock. Under-ordering means stockouts, lost sales, and unhappy customers. Achieving the ideal inventory balance\u2014ordering precisely what is required, when it is needed\u2014traditionally depended on intuition or costly software.AIGEN provides AI-driven accessibility to this precision.<\/p>\n\n\n\n

\"\"<\/figure>\n<\/div><\/div><\/div>\n\n\n\n
\n

<\/span><\/span>By training on your complete historical sales data, our models identify unique seasonality, velocity, and volatility for every SKU. These rolling demand forecasts reconcile with current stock levels to deliver actionable reorder recommendations.<\/p>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n

\n
\n

<\/span><\/span>Sales Uplift with Next Best Offer
and Next Best Channel
Prediction by AI<\/h2>\n<\/div><\/div><\/div>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\n

<\/span><\/span>AI powers NBO\/NBC by combining customer data demographics, transaction history, product holdings, digital behavior, past campaign responses with context like time since last purchase or seasonality to predict which product a customer will likely buy next and which channel (call center, app, agent, branch) they’ll likely respond through. Propensity models are typically trained per product-channel pair and ranked to serve each customer their single best match, rather than blasting all products everywhere.
More advanced setups use uplift modeling, which targets customers who’ll buy because they were contacted excluding sure-things and lost-causes so spend concentrates on persuadable customers.\u00a0<\/p>\n<\/div><\/div><\/div>\n\n\n\n

\n
\n\n

Case Study<\/h2>\n\n \n
\n\n

\n Insurance Company NBO\/NBC Deployment\n \n <\/h3>\n\n

\n Turning Historical Policy Data into Precise AI Insights\n <\/p>\n\n \n\n

\n An insurer with years of policy, claims, and interaction data across millions of customers historically ran cross-sell campaigns by broad segment (e.g., “ages 35\u201350 with a life policy”), offering everyone the same product through the same channel effectively random targeting within a bucket. Training propensity and uplift models on this historical data lets the insurer score every customer for every product-channel pair and rank by predicted conversion or incremental lift. Top-decile customers identified this way often convert at 30\u201350x the random baseline, and even weaker segments typically still land around 10x. \nThis means a campaign that once needed 100,000 contacts to hit a target conversion count can instead target a few thousand high-propensity customers for similar or better results cutting cost-per-acquisition, reducing offer fatigue, and freeing agent time for the leads worth pursuing.\n <\/p>\n\n

\n\n \n\n

\n AI evaluates every customer against every product-channel combination at a scale and consistency no team can match, without biases like favoring familiar segments or overweighting the last campaign’s results. It consistently beats manual segmentation on conversion rate and cost and improves over time as campaign outcomes feed back into retraining, unlike static human rulesets.\n <\/p>\n\n <\/div>\n <\/div>\n\n \n\n<\/section>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n\n\n

\n
\n

\u0e2b\u0e32\u0e01\u0e18\u0e38\u0e23\u0e01\u0e34\u0e08\u0e02\u0e2d\u0e07\u0e04\u0e38\u0e13\u0e01\u0e33\u0e25\u0e31\u0e07\u0e21\u0e2d\u0e07\u0e2b\u0e32\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19 AI <\/h2>\n\n\n\n

\u0e21\u0e32\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e22\u0e01\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e43\u0e2b\u0e49\u0e02\u0e31\u0e49\u0e19\u0e15\u0e2d\u0e19\u0e01\u0e32\u0e23\u0e17\u0e33\u0e07\u0e32\u0e19\u0e40\u0e1b\u0e47\u0e19\u0e41\u0e1a\u0e1a Automation \u0e41\u0e25\u0e30\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e43\u0e2b\u0e49\u0e01\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e17\u0e33\u0e07\u0e32\u0e19\u0e20\u0e32\u0e22\u0e43\u0e19\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23
\u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e17\u0e35\u0e48\u0e1b\u0e23\u0e36\u0e01\u0e29\u0e32 \u0e41\u0e25\u0e30\u0e1e\u0e32\u0e23\u0e4c\u0e17\u0e40\u0e19\u0e2d\u0e23\u0e4c\u0e04\u0e39\u0e48\u0e04\u0e34\u0e14\u0e43\u0e2b\u0e49\u0e01\u0e31\u0e1a\u0e18\u0e38\u0e23\u0e01\u0e34\u0e08\u0e02\u0e2d\u0e07\u0e04\u0e38\u0e13 \u0e1b\u0e23\u0e36\u0e01\u0e29\u0e32\u0e1e\u0e27\u0e01\u0e40\u0e23\u0e32 AIGEN (\u0e44\u0e2d\u0e40\u0e08\u0e47\u0e19)
<\/p>\n<\/div><\/div>\n\n\n\n

\n
\n
\n

CONTACT US<\/h2>\n\n\n\n

\u0e2b\u0e32\u0e01\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e43\u0e2b\u0e49\u0e04\u0e33\u0e41\u0e19\u0e30\u0e19\u0e33 \u0e15\u0e34\u0e0a\u0e21\u0e1c\u0e25\u0e34\u0e15\u0e20\u0e31\u0e13\u0e11\u0e4c\u0e2b\u0e23\u0e37\u0e2d\u0e01\u0e32\u0e23\u0e43\u0e2b\u0e49\u0e1a\u0e23\u0e34\u0e01\u0e32\u0e23\u0e01\u0e23\u0e38\u0e13\u0e32\u0e44\u0e1b\u0e17\u0e35\u0e48 contact@aigencorp.com<\/p>\n\n\n\n

\u0e1c\u0e39\u0e49\u0e40\u0e0a\u0e35\u0e48\u0e22\u0e27\u0e0a\u0e32\u0e0d\u0e02\u0e2d\u0e07\u0e40\u0e23\u0e32\u0e22\u0e34\u0e19\u0e14\u0e35\u0e43\u0e2b\u0e49\u0e04\u0e33\u0e1b\u0e23\u0e36\u0e01\u0e29\u0e32\u0e01\u0e32\u0e23\u0e19\u0e33\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19 AI \u0e44\u0e1b\u0e1b\u0e23\u0e31\u0e1a\u0e43\u0e0a\u0e49\u0e01\u0e31\u0e1a\u0e18\u0e38\u0e23\u0e01\u0e34\u0e08 \u0e40\u0e1e\u0e35\u0e22\u0e07\u0e41\u0e04\u0e48\u0e01\u0e23\u0e2d\u0e01\u0e1f\u0e2d\u0e23\u0e4c\u0e21\u0e14\u0e49\u0e32\u0e19\u0e25\u0e48\u0e32\u0e07\u0e19\u0e35\u0e49<\/p>\n<\/div><\/div><\/div>\n<\/div>\n\n\n\n

\n