Operation White Harbour
How SentraLink's AI traced a drug smuggling network from a single photo to a harbour terminal insider — across images, SMS, WhatsApp, and Skype conversations.
A Photo Tells the First Story
An investigator uploads a Cellebrite UFDR phone extraction — hundreds of files from a suspect's device. Among thousands of images, SentraLink's vision AI automatically scans every photo and flags one that matters: a photo containing weapons and drugs.
AI Capability: Computer vision automatically scans every image in the extraction, detecting weapons, drugs, and other objects of interest — no manual review of thousands of photos required.
A Skype Chat Confirms the Drug Operation
SentraLink doesn't stop at images. It cross-references the photo finding against all text communications on the device. A Skype conversation is surfaced — it discusses a drug smuggling operation involving illegal access to a terminal for a fee.
Cross-Entity Correlation: The AI connected the photo evidence (Step 1) to this text conversation by identifying shared drug-related context across different evidence types — image and chat.
WhatsApp Reveals Money Laundering — and a Name
A separate WhatsApp conversation is flagged. It discusses “washing powder” and a large sum of money in the context of cleaning money — suggesting potential money laundering. But critically, this conversation mentions a name: Wimmie.
Entity Extraction: SentraLink automatically extracts person names, amounts, and locations from every conversation — building a network of entities that can be traced across the entire case.
Who Is Wimmie? A Seemingly Innocent Conversation
SentraLink identifies “Wimmie” as a Person entity and shows all their connections. Clicking on Wimmie's node reveals their profile: multiple handles including a Skype handle, a WhatsApp number, and a UK phone number. One of Wimmie's connected conversations appears to be about a routine fruit delivery — no clear indication of illegal activity.
Cross-Entity Correlation: The name “Wimmie” extracted from the money laundering conversation (Step 3) is automatically linked to this person entity, revealing their full communication footprint — even conversations that appear innocent on the surface.
Wimmie Surfaces Again — This Time With Big Money
Another WhatsApp conversation involving Wimmie is flagged. This time, it's not about fruit. The conversation discusses delivering to a specific address with an associated cost of 100,000 EUR. The AI flags this as potential bribery or corruption — the “fruit delivery” from Step 4 is starting to look like a cover story.
Code Language Identified: “Fruit” was a code name for illegal goods — SentraLink identified and flagged the pattern. What appeared as an innocent delivery discussion in Step 4 now reveals its true meaning: a 100,000 EUR transaction for smuggled contraband. This conversation also mentions an individual referred to as “Shadow.”
Following the Thread: Who Is “Shadow”?
The name “Shadow” mentioned in Wimmie's 100K EUR conversation leads to another person entity. SentraLink has identified Shadow_ (handle: shadowman_uk) as a person connected to two key documents in the case. The investigator can now trace Shadow's involvement across the network.
Cross-Entity Correlation: A name mentioned in passing in one conversation becomes a traceable entity. SentraLink links “Shadow” across multiple conversations, revealing their role in the network — connecting the money (Step 5) to the operations (next steps).
Shadow's Skype Reveals the Drug Deal
Following Shadow's connections leads to a Skype conversation between Bristol_Tony and Shadow_. The cover language falls away — they're discussing a “13-9 deal” and the readiness of “white powder.” This is no longer ambiguous. The AI identifies it as a potential illegal drug deal.
Pattern Recognition: The “fruit delivery” from Step 4, the 100,000 EUR from Step 5, and now “white powder” — SentraLink's AI connects the dots across platforms (WhatsApp → Skype), people (Wimmie → Shadow → Bristol_Tony), and coded language to reveal the true nature of the operation.
The Final Piece: Terminal Access for Smuggling
The investigation comes full circle. An SMS conversation — flagged as HIGH RISK — explicitly discusses drug smuggling, the use of a terminal access pass, and the exchange of money for such access. Shadow isn't just a buyer — he's an accomplice with insider access to the harbour terminal, enabling the entire smuggling operation.
The Complete Picture: From a single photo of weapons and drugs → to Skype chats about terminal access → to WhatsApp conversations revealing Wimmie and Shadow → to coded “fruit deliveries” worth 100,000 EUR → to explicit drug deals involving “white powder” → to a harbour terminal insider enabling the smuggling. SentraLink traced the entire network automatically.
How SentraLink Accelerated This Investigation
🔗 Cross-Entity Correlation
Names, amounts, and locations extracted from one conversation are automatically linked to every other mention across SMS, WhatsApp, Skype, and images — revealing connections an investigator would take weeks to find manually.
🔍 Code Language Detection
SentraLink identifies when seemingly innocent terms like “fruit delivery” are used as code for illegal activity — connecting coded conversations to explicit ones to reveal the true meaning behind the language.
👁️ Multi-Modal Analysis
SentraLink doesn't just read text — it sees images, understands chat transcripts across platforms, and correlates findings across evidence types. A photo of drugs connects to a Skype chat connects to a WhatsApp message connects to a person.
⚡ Investigation Speed
437 nodes analyzed automatically from a single UFDR upload containing 1,324 items. What would take an investigator days of manual review — reading every chat, examining every photo, cross-referencing every name — SentraLink completes in minutes.