01
File and artefact analysis
Automated inspection of files and artefacts for malicious behaviour, producing output a human can act on, with reasoning attached.
Applied AI
Tools, not decks
Practical AI applied to detection, triage and analysis, built as software people actually use, including tools we give away.
In short
Rynexor builds applied AI tooling for security and operations: file and threat analysis, detection support, and internal automation. The position behind it is that basic security tooling should be reachable without an enterprise budget, which is why part of the work is released free, including a file security analysis platform intended for anyone to use.
What this covers
4 areas
02
Detection and triage support
Models used where they genuinely help (reducing alert volume, clustering related events, drafting the first pass of an incident timeline) and not where they do not.
03
Internal automation
The repetitive analysis that consumes a team's week, automated with the decision points left where they belong: with the people accountable for them.
04
Free public tooling
Security checks anyone can run without a sales conversation. Making the basic layer accessible is a position we have argued publicly, and shipping free tooling is how we put it into practice.
How it runs
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Stage 01
Define the decision
What judgement is being made, by whom, and what it currently costs in time. If that cannot be stated plainly, the problem is not ready for automation.
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Stage 02
Establish the baseline
How well the current process performs. Without it there is no way to know whether the model helped, and every result sounds impressive.
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Stage 03
Prototype narrowly
One workflow, real data, measured against the baseline. Broad pilots produce broad opinions.
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Stage 04
Measure error rates
False positives and false negatives reported separately, because they cost different things and an aggregate accuracy figure hides which one you are getting.
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Stage 05
Ship or stop
Into production with monitoring, or abandoned with the reasoning written down. A pilot that neither ships nor stops is the most expensive outcome available.
What you get
- A stated decision, baseline and success threshold agreed before building
- Working prototype evaluated against that baseline on real data
- False positive and false negative rates reported separately
- Production deployment with monitoring, or a written case for stopping
- Documentation your team can maintain without us
Questions we get asked
Is the free file analysis platform really free?
Yes: an AI-based check anyone can run on a file without cost and without a sales conversation. It exists because basic security checks should not require an enterprise budget.
Do you train models on our data?
No. Client data is used to serve that client and nothing else. Where a third-party model provider is involved it is named in the agreement before work starts, and you can object.
When is AI the wrong answer?
When the decision is rare, when being wrong is expensive and unreviewable, or when a rule would do the job. A large share of what gets proposed as an AI project is a reporting or process problem mislabelled as AI. We say so before building.
Scope it properly.
Tell us what you need covered. We will reply with what the work actually requires, including when you do not need us yet.
Start a brief