Just got back from a deep-dive demo of a competing intelligence platform (won't name-drop, but it's one of the newer ones with serious VC backing). Been a Recorded Future power user for two years, and now our whole workflow here feels like it's running on last-gen hardware.
The contrast is startling. It's not about the core data—RF's collection is still robust. It's the interface and the daily grind. The competitor had this:
* A unified search that actually understands natural language queries about threat actors and campaigns, returning a synthesized narrative, not just a list of disjointed "related" intel cards.
* Built-in, no-code automation to push specific alert types directly into our Slack channels *and* our SOAR platform with two clicks. With RF, I'm still fiddling with API docs or waiting for our overworked secops engineer.
* A visual link analysis tool that didn't feel like a separate, clunky module. You could start from a vulnerability, pivot to exploiting groups, to their infrastructure, in a single, fluid graph.
Here, I'm constantly tab-hopping between the main UI, the CTI extension, and the poorly-named "Fusion" reports. The mental overhead to connect the dots RF ostensibly collects for you is exhausting.
I'm paying a premium for what feels like a data warehouse with a mediocre front-end. The competitor's demo made our team's RF routine—which I'd defended—look like a series of manual workarounds.
So, a real question for the room: Has anyone else felt this lag? Are there configuration depths I'm missing to make RF feel less like a 2018 tool, or is the innovation just happening elsewhere now? Our renewal is up in Q4, and for the first time, I'm not automatically recommending we stick with the incumbent.
That's a pretty stark contrast you're describing. The unified search that actually writes a narrative instead of spitting out cards sounds like a game changer for day-to-day triage. I've only been using RF for about six months, and I already feel the "tab-hopping" pain you mentioned - especially when I'm trying to trace a campaign back to initial indicators.
The no-code automation part is what really caught my eye. I'm curious though - did the competitor's demo show how well that Slack integration actually works with existing alert fatigue? We've got so many channels already that anything more than a simple keyword filter would just get ignored. Did they have any smart dedup or summarization built in, or was it more of a raw firehose?
That feeling after a demo where everything just *flows* is a real gut punch. The tab-hopping is what kills efficiency, and it's not just a you problem.
You hit the nail on the head about the mental overhead. When you're bouncing between the main UI, Fusion, and extensions, you're not just consuming intel, you're doing data integration work yourself. That cognitive load adds up fast during an incident.
The no-code automation point is the killer. Waiting on an overworked engineer to hook up a basic Slack alert is exactly how good intel goes stale. Have you found any workable middle ground with RF's current tools, or is it all just manual process now?
terraform and chill
Oof, that hits close to home. The "tab-hopping" you mentioned is a real tax on time during an investigation. I've built a clunky internal Grafana dashboard just to try and mirror some of that unified visibility, pulling from RF's API and our own logs. It works, but it shouldn't be necessary.
The automation piece is the real friction. I've had some luck using Terraform to manage webhook subscriptions to their Alerting API, which at least codifies the setup. It's still miles from a two-click Slack integration, but it keeps us from manually configuring every new alert rule.
Have you tried pushing this through your account team? Sometimes a detailed, use-case breakdown from a power user lights more of a fire than generic feature requests.
terraform and chill
Yeah, that mental overhead is real. I've ended up using the API to pull everything into a custom Looker dashboard just to get a unified view. It gets me a synthesized story, but it's a ton of maintenance.
That fluid graph tool you mentioned - did it feel like a true investigation workspace, or more of a pretty visualization? I've seen demos where the graph looks amazing but you can't actually *do* anything with the nodes once you find them.
Our workaround for the automation piece has been building small Python bots with their SDK to parse alerts and push to Slack. Still code, but at least it's not raw API docs.
Data is the new oil - but it's usually crude.