We’ve Lived the Problem

Since 2016, we’ve worked inside breach response, deal diligence, regulatory review, and legal hold teams — where hundreds of millions of globally distributed files must be discovered, translated, classified, reviewed, deleted, or turned into evidence under legal, regulatory, or deal-related pressure.

We’ve supported U.S. government agencies and collaborated across PwC, other consulting firms, law firms, global enterprises, and AWS — always without a single solution capable of handling the scale and complexity.

While other AI startups are building incredible workflows, agents, and automations, we focus on the raw material that powers it all: the data.

These teams want to use AI — but can’t.

Not until the data is clean, reviewed, and fit for the task at hand.

That’s what we deliver.

Why Existing Solutions Fall Short

What put our team on the map was our ability to move fast: stitching together point-solution tools, creating what was missing, and breaking legacy, server-based systems apart to run better on modern cloud infrastructure. Even with multi-million dollar per month budgets, we were always held back by tools that weren’t built for the job. They could support discovery or action — but never both.

The core problem we solve is this: connecting discovery to action.

You can’t take the right action if you don’t know what matters — and most tools don’t help you figure that out. They surface too much, miss what’s important, and force teams through a maze of risky exports and handoffs — first to review the data, then to remediate it, and again for every step that follows.

Building What Today’s Teams Need

What we’re building at Octosight is what we always needed. It’s built for teams like the ones we led — deals, cybersecurity, forensics, legal, compliance, tax, audit, privacy — under pressure to move fast, get it right, and protect what matters.

We built it to deliver what we call Actionable Discovery: Search across messy, unstructured data. Tag what’s relevant. Take the right action — preserve, delete, or export — in place, without shifting files across tools or teams. Actionable Data Security takes it further, applying the same precision and control proactively — helping teams find and secure sensitive data before issues arise.

As generative AI and LLMs reshape expectations, teams are eager to take advantage — but most lack a trusted way to prepare their sensitive data for safe, effective use.

The “garbage in, garbage out” problem is especially real with AI. You can’t skip discovery and dump raw enterprise content into a model and expect useful results.

Automation is great — until it loads payroll files that let employees look up each other’s compensation, or pulls files from one virtual data room to answer diligence questions for an entirely different deal.

We enable teams to prepare high-quality data for LLMs manually — by design. Teams search, translate, classify by sensitivity, and tag what matters, then export only the curated data in a format optimized for their specific model and task.

Why Teams Trust Us

We stay close to the people doing the work.

We talk every week with former colleagues, clients, and partners who are still inside these projects. We hear where they struggle and where other solutions fall short. That feedback is what shapes Octosight — and it’s why teams trust us to help them deliver projects that can’t afford to go wrong.