Can you work with our existing SIEM and EDR?

Yes. The models read events through your SIEM’s API and write scores and context back into it, so analysts keep working in the tools they already use. We replace a component only if your team decides to.

How do you reduce false positives in our SIEM?

We start with your alert history and the outcome of each alert: closed as benign, escalated, or confirmed as an incident. The model learns which patterns in your environment usually turn out harmless and ranks new alerts by risk. Your analysts still see every alert, but the queue starts with the ones that need attention.

Where does our security data go during model training?

Training runs in your cloud account or on your servers, depending on your policy. Logs and incident data stay inside your environment, and we agree in advance which data our engineers can access and how.

Who makes the final decision: the model or our team?

Your team sets the rules. The model scores events and transactions, and the thresholds determine what happens next: low-risk events close automatically; high-risk ones go to an analyst. You can change those thresholds at any time.

How do we know the model still works after attackers change tactics?

We track detection quality for new incidents weekly and compare it to the launch baseline. When accuracy drops, we retrain the model on recent data, and the new version goes live after your team reviews the results.

How much historical data do we need to start?

It depends on the use case. For alert triage, a few months of SIEM data with incident outcomes is usually enough for a first model. For fraud detection, you need labeled transactions, including confirmed fraud cases. In a two-week discovery, we check your data and tell you whether it can support the project.

Home AI AI Security Solutions Development

AI Security Solutions Development Services

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CUT ALERT NOISE

Rank SIEM alerts by risk with models trained on your own incident history. Analysts start each shift with the cases most likely to be real.
CATCH UNKNOWN ATTACKS

Add behavior-based detection to network and endpoint monitoring. New malware variants and insider activity show up as deviations from normal patterns.
STOP FRAUD, KEEP CUSTOMERS

Score transactions in real time on behavior and device signals. Risky ones go to review, and legitimate customers pass without extra checks.

What We Build

AI Security Services We Provide

Biometrics Recognition Software

We build face and voice verification that confirms a user’s identity at the moment of a transaction. The same technology powers employee access control for offices and restricted areas.
Intrusion Detection Systems (IDS)

We build intrusion detection that learns the normal behavior of your network and endpoints. Deviations reach your administrators as prioritized alerts with the context needed to act.
Antivirus and Anti-Malware Software

We add behavioral analysis to your anti-malware stack so it catches new variants by what they do on the system. Suspicious processes are isolated automatically for your team to review.
Fraud Detection Systems

Rule-based fraud checks either let new schemes through or flag so many good transactions that customers leave. We build models that score each transaction on behavior and device data, with thresholds your fraud team controls.
SASE and Network Security Management

We add AI to your SASE setup so access policies adapt to user behavior and device risk in real time. A login from an unusual location triggers step-up verification automatically.
Security Information and Event Management (SIEM)

Your SIEM collects everything, and analysts spend most of the shift closing false alarms. We add models that group related events, score them by risk, and attach the context analysts need to decide.

Development Process

Our AI Security Solutions Development Process

Book a Consultation

01.

01. Requirement Analysis and Planning

We meet with your security team to map the threats you need to catch and set measurable goals for the solution. Then we agree on scope and timeline.

02.

02. Feasibility Study

We check the volume and quality of your security data and confirm that AI fits the problem. Then we assess project risks and agree on how to manage them.

03.

03. Architecture

We design the solution architecture and define how it connects to your SIEM and other security tools. Then we select the models that fit each detection task.

04.

04. Data Preparation

We collect historical security data with incident outcomes and prepare it for model training.

05.

05. Model Development and Training

Our engineers train the models and measure detection quality against your historical incidents. This baseline becomes the benchmark for every future version.

06.

06. Integration and Deployment

We connect the solution to your security infrastructure and deploy it to production. From day one, we monitor detection quality and model behavior.

07.

07. Compliance, Security Checks, and Maintenance

We verify compliance with the cybersecurity regulations that apply to your industry and audit the security of the solution itself. As attackers change tactics, we retrain the models on recent data to keep detection accurate.

01. Requirement Analysis and Planning
02. Feasibility Study
03. Architecture
04. Data Preparation
05. Model Development and Training
06. Integration and Deployment
07. Compliance, Security Checks, and Maintenance

How We Can Build Your Security Capability

Choose the Setup That Fits Your Security Roadmap

Discovery Sprint

We define where AI can strengthen security first.

We look at the threats you need to catch faster and the data your security systems already produce. From there, we shape a practical use case and define what the first build should cover before we invest more in development.

Good fit when: You see potential for AI in security but need a clear use case and scope before building.

Project-Based Delivery

We take the security solution through production.

For a defined scope, we own the build from architecture through integration and release. The work stays focused on a specific security problem, such as faster threat detection or more consistent response, while your team stays close to the decisions that matter.

Good fit when: You have a defined security use case and want one team accountable for getting it into production.

Dedicated Team

We keep building as the threat landscape changes.

A dedicated team works best when security development is an ongoing effort, not a one-off project. The same engineers stay close to your environment and keep improving the system as new threats appear and priorities shift.

Good fit when: You have a long-term security roadmap and need stable engineering capacity behind it.

Build-Operate-Transfer (BOT)

We build the security team. You take it in-house.

We assemble the team and run delivery while the engineers learn your environment and establish a working development model. Once the team is operating well on its own, we transfer it to your company with that knowledge already in place.

Good fit when: You want to build an internal AI security capability without staffing and structuring it from zero.

Staff Augmentation

You lead the roadmap. We add the expertise.

If your security program is already running, we add engineers who can work inside your existing team and help move specific initiatives forward. They join your process without changing who owns priorities or delivery.

Good fit when: You already have the roadmap and need stronger technical depth or more capacity.

Benefits

Benefits of Implementing AI Security Solutions

Coverage Outside SOC Hours

Models analyze events around the clock and keep scoring alerts overnight. Your analysts start each shift with a ranked queue.
Detection of New Attack Patterns

Behavior-based models flag activity that deviates from your normal patterns, so new attack techniques surface before signatures exist.
Fewer False Alarms

Models trained on your alert history learn which patterns turn out harmless in your environment. Analysts spend their time on the alerts that matter.
Fewer Blocked Customers

Transaction scoring uses behavior and device data along with fixed rules. More legitimate payments pass automatically, and your fraud team reviews the rest.

Case Studies

Our Latest Works

View All Case Studies

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An enterprise-grade automation platform that streamlines IT project workflows through smart dashboards.

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Humanising Autonomy: Behavioral AI SDK for Humanized Driver Assistance Systems (HDAS)

AUTONOMOUS DRIVING
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COMPUTER VISION
AI OPTIMIZATION
ETHICAL AI

LOGISTICS & AUTOMOTIVE

Humanising Autonomy: Behavioral AI SDK for Humanized Driver Assistance Systems (HDAS)

A computer vision SDK for predicting road user behavior and enhancing driver safety.

Additional Info

Core Tech:

C++
OpenCV
CUDA
Github Actions
Cmake
Conan
TensorRT
ONNX
Ambarella

Country:

United Kingdom

View Case Study

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Awards & Certifications

Industry Contribution Awards & Certifications

Check Devox Software’s awards on rating and review platforms, recognized among the top software development companies, along with the certifications our team members hold.

Awards
Certifications

UpWork
Clutch
The Manifest
DesignRush
MC.today
Clutch
Clutch
AppFutura
Clutch
GoodFirms
DesignRush
UpWork

Claude Certified Developer - Foundations (CCDV-F)
Claude Certified Partner
Certified Kubernetes Application Developer (CKAD)
Cisco CCNA certification
Microsoft Certified: DevOps Engineer Expert
Quality Assurance ISTQB Foundation Level
Java Development Certified Professional
Certified Artificial Intelligence Scientist (CAIS)
Oracle Database SQL Certified Associate
ITSMS Auditor/Lead Auditor of ISO Standard 20000
Microsoft Certified: Azure Fundamentals (AZ 900)
PL-400: Power Platform Developer Associate
Professional Scrum Product Owner™ I (PSPO I)
Professional Scrum Master™ II (PSM II)

Testimonials

Sweden

The solutions they’re providing is helping our business run more smoothly. We’ve been able to make quick developments with them, meeting our product vision within the timeline we set up. Listen to them because they can give strong advice about how to build good products.

Carl-Fredrik Linné

Tech Lead at CURE Media

View on Clutch

United States

We are a software startup and using Devox allowed us to get an MVP to market faster and less cost than trying to build and fund an R&D team initially. Communication was excellent with Devox. This is a top notch firm.

Darrin Lipscomb

CEO, Founder at Ferretly

View on Clutch

Australia

Their level of understanding, detail, and work ethic was great. We had 2 designers, 2 developers, PM and QA specialist. I am extremely satisfied with the end deliverables. Devox Software was always on time during the process.

Daniel Bertuccio

Marketing Manager at Eurolinx

View on Clutch

Australia

We get great satisfaction working with them. They help us produce a product we’re happy with as co-founders. The feedback we got from customers was really great, too. Customers get what we do and we feel like we’re really reaching our target market.

Trent Allan

CTO, Co-founder at Active Place

View on Clutch

United Kingdom

I’m blown up with the level of professionalism that’s been shown, as well as the welcoming nature and the social aspects. Devox Software is really on the ball technically.

Andy Morrey

Managing Director at Magma Trading

Switzerland

Great job! We met the deadlines and brought happiness to our customers. Communication was perfect. Quick response. No problems with anything during the project. Their experienced team and perfect communication offer the best mix of quality and rates.

Vadim Ivanenko

COO at Optherium

View on Clutch

United States

The project continues to be a success. As an early-stage company, we're continuously iterating to find product success. Devox has been quick and effective at iterating alongside us. I'm happy with the team, their responsiveness, and their output.

Jason Leffakis

Founder, CEO at Function4

View on Clutch

Sweden

We hired the Devox team for a complicated (unusual interaction) UX/UI assignment. The team managed the project well both for initial time estimates and also weekly follow-ups throughout delivery. Overall, efficient work with a nice professional team.

John Boman

Product Manager at Lexplore

View on Clutch

Canada

Their intuition about the product and their willingness to try new approaches and show them to our team as alternatives to our set course were impressive. The Devox team makes it incredibly easy to work with, and their ability to manage our team and set expectations was outstanding.

Tamas Pataky

Head of Product at Stromcore

View on Clutch

Estonia

Devox is a team of exepctional talent and responsible executives. All of the talent we outstaffed from the company were experts in their fields and delivered quality work. They also take full ownership to what they deliver to you. If you work with Devox you will get actual results and you can rest assured that the result will procude value.

Stan Sadokov

Product Lead at Multilogin

United Kingdom

The work that the team has done on our project has been nothing short of incredible – it has surpassed all expectations I had and really is something I could only have dreamt of finding. Team is hard working, dedicated, personable and passionate. I have worked with people literally all over the world both in business and as freelancer, and people from Devox Software are 1 in a million.

Mark Lamb

Technical Director at M3 Network Limited

FAQ

Can you work with our existing SIEM and EDR?

Yes. The models read events through your SIEM’s API and write scores and context back into it, so analysts keep working in the tools they already use. We replace a component only if your team decides to.
How do you reduce false positives in our SIEM?

We start with your alert history and the outcome of each alert: closed as benign, escalated, or confirmed as an incident. The model learns which patterns in your environment usually turn out harmless and ranks new alerts by risk. Your analysts still see every alert, but the queue starts with the ones that need attention.
Where does our security data go during model training?

Training runs in your cloud account or on your servers, depending on your policy. Logs and incident data stay inside your environment, and we agree in advance which data our engineers can access and how.
Who makes the final decision: the model or our team?

Your team sets the rules. The model scores events and transactions, and the thresholds determine what happens next: low-risk events close automatically; high-risk ones go to an analyst. You can change those thresholds at any time.
How do we know the model still works after attackers change tactics?

We track detection quality for new incidents weekly and compare it to the launch baseline. When accuracy drops, we retrain the model on recent data, and the new version goes live after your team reviews the results.
How much historical data do we need to start?

It depends on the use case. For alert triage, a few months of SIEM data with incident outcomes is usually enough for a first model. For fraud detection, you need labeled transactions, including confirmed fraud cases. In a two-week discovery, we check your data and tell you whether it can support the project.

Book a call

Want to Achieve Your Goals? Book Your Call Now!

We Fix, Transform, and Skyrocket Your Software.

Tell us where your system needs help — we’ll show you how to move forward with clarity and speed. From architecture to launch — we’re your engineering partner.

Book your free consultation. We’ll help you move faster, and smarter.

Let's Discuss Your Project!

Share the details of your project – like scope or business challenges. Our team will carefully study them and then we’ll figure out the next move together.

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Achievements

About Us

Careers

AI Security Solutions Development Services

AI Security Services We Provide

Biometrics Recognition Software

Intrusion Detection Systems (IDS)

Antivirus and Anti-Malware Software

Fraud Detection Systems

SASE and Network Security Management

Security Information and Event Management (SIEM)

Our AI Security Solutions Development Process

01. Requirement Analysis and Planning

02. Feasibility Study

03. Architecture

04. Data Preparation

05. Model Development and Training

06. Integration and Deployment

07. Compliance, Security Checks, and Maintenance

Choose the Setup That Fits Your Security Roadmap

Discovery Sprint

Project-Based Delivery

Dedicated Team

Build-Operate-Transfer (BOT)

Staff Augmentation

Benefits of Implementing AI Security Solutions

Coverage Outside SOC Hours

Detection of New Attack Patterns

Fewer False Alarms

Fewer Blocked Customers

Our Latest Works

AI-Powered Social Media Background Check Platform for Risk-Free Hiring

Juriba: Enterprise Digital Workplace Management Platform for Migration & Automation

Humanising Autonomy: Behavioral AI SDK for Humanized Driver Assistance Systems (HDAS)

Trusted by

Industry Contribution Awards & Certifications

Testimonials

Carl-Fredrik Linné

Darrin Lipscomb

Daniel Bertuccio

Trent Allan

Andy Morrey

Vadim Ivanenko

Jason Leffakis

John Boman

Tamas Pataky

Stan Sadokov

Mark Lamb

FAQ

Can you work with our existing SIEM and EDR?

How do you reduce false positives in our SIEM?

Where does our security data go during model training?

Who makes the final decision: the model or our team?

How do we know the model still works after attackers change tactics?

How much historical data do we need to start?

Want to Achieve Your Goals? Book Your Call Now!

We Fix, Transform, and Skyrocket Your Software.

Let's Discuss Your Project!

Thank You for Contacting Us!

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