Aegis-1 is our flagship security AI — a specialized model we engineered in-house, from the ground up, for one domain. It runs entirely on your own infrastructure, helping your team sort alerts, decide what to fix first, and ship safer code, while everything sensitive stays inside your walls.
Illustrative, anonymized examples — the industry, what we built, and the value it delivered.
The problem. The bank's security team was buried in alerts, spending most of the day looking things up and writing notes instead of investigating threats. Strict data rules kept public AI tools off the table.
What we built. An assistant beside the team's existing alert system, running entirely inside the bank's network. When an alert arrives, Aegis-1 drafts what happened in plain language, whether it looks like a real threat or a false alarm, relevant background, and suggested next steps drawn from the bank's own playbooks. Guardrails: it must always show its sources, it can never invent a flaw ID, and containment always waits for a person.
| Before | After | |
|---|---|---|
| Time to a solid first investigation note | 25–40 minutes | 6–10 minutes |
| Drafts analysts actually use | — | ~70%+, with light edits |
| Sensitive alert data | Risk if sent to public AI | Stays inside the bank |
The problem. Security scans turned up thousands of issues. Teams patched whatever scored highest on a raw severity scale — often the wrong things first. When a flaw hit the news, answering "are we exposed?" took days, and plant maintenance windows are rare and expensive.
What we built. An assistant layered on the plant's existing scanning tools and equipment records. Aegis-1 produces a weekly "fix these first" list with plain-language reasons, fast memos answering "this flaw is in the news — are our machines affected?", and draft repair tickets once a person signs off. The risk scoring stays in ordinary, deterministic software; Aegis-1 explains and ranks within that real data, grounded in equipment that actually exists.
| Before | After | |
|---|---|---|
| Building the weekly "what to fix" list | 2–3 days of expert time | 3–5 hours reviewing a draft |
| Answering "are we affected?" on breaking news | 1–3 days | ~15–30 minutes |
| Wrong equipment names in reports | A manual spreadsheet risk | Blocked automatically |
The problem. Code shipped every week, but security review happened late. Automated scanners flagged so much noise that developers learned to ignore them — and company policy kept proprietary code out of public AI tools. The security team became a bottleneck.
What we built. A private assistant built into the normal code-review process. On every proposed change, Aegis-1 reviews what changed, leaves a small number of genuinely useful comments, suggests a fix and a way to test it, and can outline what could go wrong in a new service. The security team still sets severity and grants exceptions; developers still decide when to ship.
| Before | After | |
|---|---|---|
| First useful security feedback | Days, waiting on a person | Minutes, automatically |
| Comments developers act on | Low — tools were noisy | ~65–75%, after tuning |
| Proprietary code and public AI | A policy conflict | Everything stays private |
The same private model, applied across the daily work of a security operation.
Sort the day's alerts and log anomalies into "look now," "routine," and "background noise" — with the reasoning shown.
Turn thousands of scan findings into a short, defensible "fix these first" list, mapped to the systems you actually run.
A private reviewer on every change — focused comments, suggested fixes, and a way to test them.
First drafts of incident summaries, timelines, and response steps — grounded in your own playbooks, ready for a person to finish.
When a flaw makes the news, a same-morning memo on your actual exposure — instead of a days-long scramble.
Consistent, sourced notes on every investigation — the paper trail your auditors and regulators ask for.
| Banking | Manufacturing | SaaS / Software | |
|---|---|---|---|
| What we built | Alert investigation assistant | Priority list + exposure memos | Code reviewer + risk outlines |
| Who decides | Contain or escalate | Patch or accept the risk | Merge or grant exception |
| Headline result | 25–40 min → 6–10 min per note | Days → hours for the weekly list | Days → minutes for feedback |
Our research paper explains why serious security demands a model designed for the domain from the first token — specialized, efficient, and governed responsibly.
Private, precise security intelligence that runs where your data already lives — with your team, and your people, always in control.
Talk to us about Aegis-1