You will get Behavioural anomaly detection for the data your systems already emit
Project details
Fixed thresholds fail in both directions. Set them tight and the channel fills with noise until someone mutes it. Set them loose and the real failure slips under the line. Either way, six months later nobody reads the alerts.
The alternative is to model what normal looks like in your system specifically, from your own history, and flag what departs from it. Normal for a factory line at 3am is not normal at noon. Normal for your transaction volume on the last business day of the month is not normal on a Tuesday. A threshold cannot know that. A baseline built from your data can.
The first package is an audit rather than a build. What your existing telemetry can already detect, what it cannot, and what would need to start being recorded. That report is useful whether or not you continue.
Then the detectors, calibrated on your history, with the false positive rate measured against periods you know were fine. A detector nobody trusts is a detector everyone eventually ignores, which is how you got here.
This is the same work I do in game security, where the question is whether a player's behaviour is humanly plausible. The domain changes, the statistics do not.
The alternative is to model what normal looks like in your system specifically, from your own history, and flag what departs from it. Normal for a factory line at 3am is not normal at noon. Normal for your transaction volume on the last business day of the month is not normal on a Tuesday. A threshold cannot know that. A baseline built from your data can.
The first package is an audit rather than a build. What your existing telemetry can already detect, what it cannot, and what would need to start being recorded. That report is useful whether or not you continue.
Then the detectors, calibrated on your history, with the false positive rate measured against periods you know were fine. A detector nobody trusts is a detector everyone eventually ignores, which is how you got here.
This is the same work I do in game security, where the question is whether a player's behaviour is humanly plausible. The domain changes, the statistics do not.
Machine Learning Tools
MLflow, NumPy, pandas, Python, Python Scikit-Learn, SciPy, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$900
|
Standard
$2,400
|
Advanced
$4,800
|
|---|---|---|---|
| Delivery Time | 10 days | 20 days | 32 days |
Number of Revisions | 2 | 4 | 6 |
Number of Model Variations | 1 | 2 | 6 |
Number of Scenarios | 2 | 5 | 10 |
Number of Graphs/Charts | 3 | 8 | 15 |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$400 - $2,100
Additional Revision
+$220
Additional Model Variation
(+ 4 Days)
+$400
Additional Scenario
(+ 4 Days)
+$500
Additional Graph/Chart
(+ 1 Day)
+$150
Data Source Connectivity
(+ 5 Days)
+$600
Historical backfill
(+ 6 Days)
+$700
Root cause correlation
(+ 8 Days)
+$900
Seasonality handling
(+ 6 Days)
+$700Frequently asked questions
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HW
Huitong W.
Jun 16, 2025
C++ Game Development
Very good Developer!
HW
Huitong W.
Oct 20, 2024
Next Game Development
Very Good
HW
Huitong W.
Jul 1, 2024
Implement NavPower in GameEngine.
HW
Huitong W.
May 14, 2024
C++ game Development
Very good developer.
We are about to start more contracts.
We are about to start more contracts.
CG
Chris G.
Mar 8, 2024
Desktop .EXE Application Development for Data Simulator
Was a pleasure working with Francisco! A+++ work and was able to help develop our application very quickly and effectively. Would highly recommended!
About Francisco
Security & Systems Engineer | C/C++, Anti-Cheat, Infrastructure
100%
Job Success
Novo Hamburgo, Brazil - 5:04 pm local time
What I do for clients falls into four areas. Game integrity: anti-cheat detection built on behaviour rather than signatures, client-side and server-side, with the evidence behind every flag. Native engineering: C++17 and C++20 systems, stable C ABI layers and language bindings, legacy modernization, and the profiling to prove a change actually helped. Security: application and infrastructure audits ranked by what an attacker can reach rather than by a generic score. Infrastructure: VMware assessment, migration planning to Proxmox or Hyper-V, and backup designs that get tested instead of assumed.
Different domains, same question underneath. What breaks, under what conditions, and who pays for it when it does. That is the question I am useful for, whether the answer lives in a memory allocator, a permission model or a renewal quote.
I also build products under TypeName Studios, which is where that standard comes from. Praetor is a game integrity platform with a C++ SDK that links into the game server and runs statistical detectors without a kernel driver or a client agent. Ethereal is the C++ middleware underneath everything I ship, thirty one modules exposed through a C ABI so it embeds into non-C++ codebases. Living with those architectural decisions for years changes how you make them.
I ask the hard questions before writing a line of code, because the wrong architecture costs far more than the wrong syntax. You get direct communication, realistic timelines, and code your team can still read a year from now. Tell me what you are trying to build and I will tell you straight whether I am the right person for it.
Steps for completing your project
After purchasing the project, send requirements so Francisco can start the project.
Delivery time starts when Francisco receives requirements from you.
Francisco works on your project following the steps below.
Revisions may occur after the delivery date.
Signal audit
I go through what your systems already emit and work out which deviations are detectable with it today, and which would need new instrumentation. You get that in writing before anything is built.
Baseline from your history
Normal is modelled from your own data, including the cycles that look like anomalies and are not. Night shift, month end and seasonal peaks stop firing, which is most of what makes alerts readable.