Automate log redaction and anomaly detection. Paste your logs, get instant results. No installs, no account needed.
Paste your data, click once, get results. Built for the middle of an incident, not ideal conditions.
Automatically masks sensitive data from network logs before sharing with vendors, TAC teams, or colleagues. IPs, MACs, credentials, hostnames, and BGP community strings stripped in seconds with consistent tokenization.
Paste any network log or telemetry data and get an AI-powered analysis in seconds. Detects BGP anomalies, DDoS patterns, interface errors, and security threats with severity ratings and specific recommended actions.
No logins, no configuration, no learning curve.
Copy raw output directly from your router, firewall, or monitoring system and paste it in. Any format works.
Choose environment, network type, and focus area. The AI adjusts its analysis to your situation.
Receive severity-coded findings with specific, actionable recommendations ready to act on or share with your team.
A full walkthrough of how to build and ship production-grade network config management. Real Python code, Jinja2 templates, telemetry pipelines, infrastructure as code, team collaboration patterns, and an interactive config generator.
No account needed. Just paste your log and go.
This site started as a personal project to solve a real problem I faced regularly in network operations. Here is the full honest story of how it came together, the tools I used, and what I learned along the way.
I registered networkforai.com through IONOS. The setup was straightforward and they included a free business email address for the first month. After the trial, the email plan is around $5 per month. The domain registration itself is reasonably priced and the IONOS dashboard is clean and easy to manage DNS records from.
IONOS does not include a free SSL certificate, which means the site would show "Not Secure" in the browser. I moved the hosting to Netlify, which solved this completely. Netlify provisions a free Let's Encrypt SSL certificate automatically, handles global CDN distribution, supports instant deploys by drag and drop, and has a generous free tier with 100GB bandwidth per month. It was the right call.
The log redactor is built with Python regex patterns running entirely in the browser via JavaScript. I mapped out every sensitive data type that appears in network logs including IPv4 and IPv6 addresses, MAC addresses, BGP community strings, hostnames, and credentials, then wrote regex rules to detect and replace each one. Tokenization ensures the same IP always maps to the same token so the log stays readable while all sensitive data is masked.
The anomaly detector sends your log to Google Gemini, a large language model, which reads and understands the log the same way an experienced engineer would. It identifies patterns, correlates events, assigns severity levels, and generates actionable recommendations. This kind of reasoning is not possible with regex alone and is where AI genuinely adds value on top of traditional rule-based approaches.
These tools were built for individual engineers but the same problems exist at scale inside organizations. Here is how teams and companies can put them to work immediately.
Engineers can redact logs before escalating to vendors or TAC in seconds instead of spending 10 to 15 minutes manually scrubbing each file. The anomaly detector gives a first-pass triage during incidents when speed matters most.
Consistent automated redaction removes the human error risk from log sharing. Every sensitive field is masked before data leaves the organization, supporting data handling policies and vendor security requirements without slowing down the team.
Junior engineers can paste real logs into the anomaly detector and immediately see a structured explanation of what each issue means and what to do about it. This accelerates skill development without requiring a senior engineer to explain every incident from scratch.
If your organization wants a customized version of these tools, with your own branding, internal hosting, a backend API proxy so engineers do not need personal API keys, or integration with your existing ticketing and monitoring systems, I am open to conversations. Reach out at [email protected]
I am actively planning the next set of tools based on real problems I have seen in network operations. Here is what is on the roadmap.
Paste a BGP configuration and get an AI review of potential misconfigurations, missing route policies, and security risks before pushing to production.
Paste a change request or diff and get a plain-English summary of what is changing, what the risk is, and what rollback steps should look like.
An interactive tool that walks through a structured troubleshooting flow for OSPF adjacency failures and BGP session issues, guiding engineers step by step.
Describe an incident type and the tool generates a draft runbook with escalation steps, verification commands, and rollback procedures tailored to your environment.
This is a project built by a working network engineer, not a startup with a product team. Every piece of feedback goes directly to me and genuinely shapes what gets built next. If you have ideas, find a bug, or want to suggest a tool, I want to hear it.
Are there repetitive tasks in your daily network operations work that still require too much manual effort? Configuration auditing, capacity reporting, vendor communication templates, something else entirely? Let me know and I will consider building it.
If your organization handles a high volume of vendor escalations, TAC cases, or internal log sharing and you think these tools could fit into your workflow, I am open to discussing a customized or self-hosted version.
If a sample log does not load, a redaction pattern misses something, or the anomaly detector returns an unexpected result, please send the details. Bug reports are just as valuable as feature ideas.