PRODUCTAI FOR IGAMING
AI that thinks in iGaming.
Most AI tools are generic. They don't understand odds movement, RTP deviation, casino volatility, bonus abuse patterns or the regulatory context that wraps this industry. The Gamblitude AI Agent was built for iGaming logic and runs directly on your governed data warehouse, so it answers real operational questions, watches the business continuously and writes the reports itself. On the platform, or in Slack, Telegram, Microsoft Teams and Google Chat, wherever your team already talks.
WHY GENERIC AI FAILS IN IGAMING
A confident answer is not a correct answer.
This domain is too fast, too specialised and too behaviourally specific to learn from the open internet. Bolt a general-purpose model onto a BI stack and it fails in four predictable ways, each one fluent, plausible and expensive.
FIG. 00 · FOUR FAILURE MODES
01
// THE VOCABULARY
It doesn't speak the domain.
Odds movement, margin formation, session economics, RTP, the deposit-bonus-withdrawal relationship: a general model has read about them, but it has never operated on them. Its answers sound right and reason wrong.
◆ COST: FLUENT NONSENSE IN A MEETING NOTE
02
// THE HALLUCINATION
LLM-on-raw-SQL invents KPIs.
Point a model at raw tables and it guesses which column is NGR, which rows count as active players, which timezone the day ends in. Every guess is a new, unversioned KPI definition, delivered with total confidence.
◆ COST: DECISIONS BUILT ON INVENTED NUMBERS
03
// THE STALENESS
It reasons about yesterday.
Live markets carry real risk exposure by the minute. An AI that reads overnight extracts or cached exports answers every question about a business that no longer exists, while liability builds in the one that does.
◆ COST: RISK MOVES FASTER THAN THE ANSWER
04
// THE BLACK BOX
You can't defend the answer.
Regulators, auditors and boards ask one question: where did this number come from? If the trail ends at "the model said so", the answer is unusable. In a licence review, that's not a small inconvenience.
◆ COST: INSIGHT YOU CANNOT PUT ON RECORD
GAMBLITUDE AI IS GROUNDED, LIVE AND AUDITABLE, BECAUSE OF HOW IT IS BUILT, NOT HOW IT IS PROMPTED
HOW YOU USE THE AGENT
One agent. Three ways of working.
Ask it a question, let it watch the business for you, or let it write the reports. All three modes read the same governed Metrics, so the answer is the same no matter which door you come through.
FIG. 01 · THREE MODES
01 Chat with the AgentAsk anything, in plain language
02 Insight RadarThe agent watches, so you don't have to
03 Reports & Scheduled ReportsThe report writes itself, on your calendar
EVERY MODE · EVERY CHANNEL
PLATFORMSLACKTELEGRAMMS TEAMSGOOGLE CHATE-MAIL
Chat, alerts and scheduled reports reach your team wherever it already talks: same agent, same governed numbers.
MODE 01 · CHAT
ask("why?") → answer + evidence
Chat with the Agent
The standard mode: a conversation with an analyst who has already read all your data. The agent understands your Metrics, your Attributes, your data model and how iGaming behaves, and it runs directly on the data warehouse, so answers stay fast and your data stays contained.
Ask operational questions in plain language: "why did margin drop yesterday?"
Drill down through provider, game, league, market or segment in follow-ups
Compare performance across time ranges and cohorts without writing a query
Every answer carries its evidence: the KPI version and the events behind it
OUTCOMEanswers in secondsevidence attachedno SQL
MODE 02 · INSIGHT RADAR
IF anomaly THEN alert(context)
Insight Radar
Proactive mode: the agent monitors the business continuously and speaks up only when something matters. Each alert arrives with context, probable causes and recommended next steps, so you stop staring at dashboards waiting for something to go wrong.
Margin shifts, RTP deviation, withdrawal patterns, traffic-quality drops: watched around the clock
Schedule your own checks in plain language: "every day at 9:00, list deposits over €5,000"
Alerts delivered where you work: platform, Slack, Telegram, Microsoft Teams, Google Chat or e-mail
Answer an alert with a question, and the conversation continues right there
OUTCOMEalways oncontext includedsignal, not noise
MODE 03 · REPORTS
cron("Mon 09:00") → report.pdf
Reports & Scheduled Reports
Document mode: ask for a report and a full first draft, charts, narrative and commentary included, is ready in seconds. Put it on a schedule and it becomes a standing deliverable: the Monday-morning executive summary that nobody had to stay late on Friday to write.
Full first drafts in seconds: performance summaries, deep dives, trading & risk reviews
Scheduled reports land automatically: weekly exec summary, Monday 09:00, every Monday
Delivered in-platform, as polished PDF, by e-mail, or straight into your messengers
Numbers always match the dashboards: same Metric Engine underneath
OUTCOMEdrafts itselfon schedulealways consistent
ANY CHANNEL, ONE TRUTH
Ask from anywhere. The answer never changes.
The CEO asks on the way to the airport. The trading desk asks from its channel. The analyst asks on the platform. Every route leads to the same Metric Engine, so everyone gets the same number, computed the same way, at the same moment.
FIG. 02 · ONE AGENT, EVERY MESSENGER
CHANNEL · 01
Slack
Chat with the agent in any channel or DM. Insight Radar alerts and scheduled reports land where the team already coordinates.
CHANNEL · 02
Telegram
The mobile favourite. Ask a question from anywhere and get governed numbers back in seconds: ideal for founders and executives on the move.
CHANNEL · 03
Microsoft Teams
For organisations that live in the Microsoft ecosystem: the agent joins your Teams workspace like any other colleague.
CHANNEL · 04
Google Chat
Native in Google Workspace. Ask, get alerted and receive reports without leaving the tools your teams work in all day.
PLUS THE PLATFORM AND E-MAIL: ONE NUMBER, NO MATTER WHO ASKS, OR WHERE
AI ACROSS EVERY WORKFLOW
Not a chatbot bolted on. Woven through.
Because the agent is part of the ecosystem, it quietly upgrades every module you already use. There is no separate AI product to license, configure, secure or maintain.
FIG. 03 · SEVEN QUIET UPGRADES
Segments: smarter segmentation generated from live behaviour
Metrics: assisted KPI creation and validation, still fully governed
Reports: executive summaries and deep dives drafted automatically
Dashboards: contextual hints and surfaced insights on every view
Targets: early warnings the moment performance starts drifting
Data Sheets: investigation notes generated as you work
Search by ID: a raw identifier becomes a full behavioural profile
ONE INTEGRATION ACTIVATES
AI IN EVERY MODULE AT ONCE
AI IN EVERY MODULE AT ONCE
HOW GOOD AI FOR IGAMING MUST BE BUILT
The agent is only as honest as the stack beneath it.
Grounded AI isn't a prompt-engineering trick. It's an architecture. The agent stands on three layers: one shared data warehouse where all verticals land in a single model, a governance layer where every Metric and Attribute has exactly one versioned definition, and a semantic layer that translates business language into that model. Remove any layer and you're back to a chatbot guessing at column names.
Every answer traces back through all three layers, to the KPI definition, and to the raw events underneath it.
ONE DATA WAREHOUSEGOVERNED METRICS + ATTRIBUTESSEMANTIC LAYERLOCAL INFERENCE
FIG. 04 · THE GROUNDED STACK
// YOUR ENVIRONMENT: DATA NEVER LEAVES FOR INFERENCE
L4
AI Agent
Chat · Insight Radar · Reports: every mode, every channel
L3
Semantic layer
Business language mapped to the data model: "margin" means one thing
L2
Governance: Metric Engine + Attributes
One versioned, audited definition per KPI and per entity attribute
L1
Shared data warehouse
Sportsbook · casino · payments · CRM · affiliates: billions of events, live
✕ LLM BOLTED ONTO RAW TABLES
Guesses KPI definitions per question: a new NGR every time
Reasons over stale extracts while live risk builds
Ships your data out for inference, then can't explain the answer
✓ AGENT ON THE GROUNDED STACK
Computes through the Metric Engine: zero invented KPIs
Reads the live data warehouse: its view is always current
Local inference, every answer traceable to definition and events
03MODES ·
ONE AGENT
ONE AGENT
00TRAINING PERIOD ·
READY DAY ONE
READY DAY ONE
100%ANSWERS TRACEABLE
TO GOVERNED KPIS
TO GOVERNED KPIS
24/7INSIGHT RADAR
ON WATCH
ON WATCH
01INTEGRATION ·
AI EVERYWHERE
AI EVERYWHERE
LOCAL INFERENCE: YOUR DATA NEVER LEAVES THE ENVIRONMENTISO/IEC 27001 CERTIFIED
01Does our data leave the environment for AI inference?
+
No. All inference runs locally, on your governed data warehouse inside the platform environment. Nothing is shipped to a third-party model for answering, which is why responses stay fast and why compliance, security and audit stay comfortable.
02How do you prevent hallucinated numbers?
+
The agent never computes a KPI itself. Numbers come from the Metric Engine, one versioned, audited definition per metric, and the agent reasons on top of them through the semantic layer. Every answer is traceable back to the definition and the raw events, so there is nothing for the model to invent.
03Which messengers does the agent work in?
+
All three modes, chat, Insight Radar alerts and scheduled reports, work in Slack, Telegram, Microsoft Teams and Google Chat, alongside the platform and e-mail. Same agent, same governed numbers, whichever channel your team already uses.
04How do scheduled reports work?
+
Describe what you want and when, in plain language: "weekly executive summary, every Monday at 9:00" or "daily trading recap after close". The agent drafts the report on schedule and distributes it to the platform, e-mail or your messenger of choice. The numbers always match the dashboards, because both read the same Metric Engine.
05How long until the AI is useful, is there a training period?
+
None. The agent is grounded in your Metrics, Attributes and data model from the moment the platform is integrated, so accurate answers arrive from day one. No fine-tuning exercises, no learning curve, no "give it a quarter".
EXPLORE THE PLATFORM
The AI is one layer of the platform
ONE PLATFORM · ONE SOURCE OF TRUTH
// ASK. WATCH. REPORT.
Put an analyst in every chat window: one you can audit.
Bring one real question from yesterday's operations. We'll ask the agent live, on governed data, and trace the answer back to the definition together.
Book a demo now