Company Profile
Whatfix: When Security Has to Move at the Speed of the Business
Whatfix is an AI-native digital adoption platform that maximizes software ROI with in-app guidance, simulation training, and adoption analytics. As its infrastructure scaled across cloud environments, identity systems, and SaaS integrations, the security challenge wasn't just technical, it was operational. A lean, high-velocity team couldn't afford to run security from a separate tool that nobody checked in real time.
The answer wasn't to hire a bigger SOC. It was to bring the entire SecOps engine inside the collaboration layer where the team already worked and let autonomous agents handle everything else. That vision led them to Trench Security's Agentic AI System.
Challenges
The Problem: Reactive Security, Blind Spots, and a SOC Disconnected from the Team
Whatfix's security posture was constrained by the limits of traditional, rule-based operations. Detection logic was untuned, hunting was time consuming, and security workflows lived in multiple tools and email threads entirely separate with poor context from where the team made decisions.
Untuned Detection Rules at Scale
Thousands of SIEM rules were active without lifecycle management, MITRE mapping, or performance review producing low-fidelity signals with no way to distinguish precision detections from noise generators.
Limited Attack Surface Coverage
Coverage across cloud, identity, endpoint, network, and SaaS was fragmented. Without a unified view, visibility gaps across MITRE ATT&CK tactics went undetected and unaddressed.
No Continuous Threat Hunting
Proactive hunting required manual effort and analyst availability: a luxury a lean team rarely had. Threats were only found if they announced themselves.
SecOps Isolated from Where the Team Works
Security alerts lived in separate tools and email threads, disconnected from the collaboration layer where decisions were made. Constant context switching slowed every response.
Transformation
From Static Rules to an Agentic Detection & Automation Engine
Before Trench
- Limited monitoring coverage and visibility gaps
- Detection rules accumulated without systematic tuning or MITRE mapping
- Fragmented MITRE coverage, blind to attack surface
- No proactive threat hunting
- Email alerts, no workflow structure
- Manually maintained institutional knowledge or playbooks
After Trench
- 24x7 autonomous monitoring powered by Agents
- High-fidelity detections, high-quality investigations
- 100% visibility on blindspots and coverage gaps
- Continuous autonomous hunting at scale
- 100% workflows automated end-to-end via Slack
- Self-learning knowledge base across all playbooks and new scenarios
Adoption Story
How the Whatfix SOC Team Made Trench Their Own
Trench deployed alongside Whatfix's existing environment with no rip-and-replace and no downtime. But the real shift wasn't technical, it was operational. For the first time, Whatfix's complete SecOps engine moved inside Slack: the collaboration layer where their team already worked, made decisions, and moved fast.
Detection findings, investigation workflows, hunt results, and response actions - all of it now flows directly into the channels where the team operates. The right signal reaches the right person with full context, without a portal login or context switch. Security stopped being something the team went to check. It became something that came to them.
On the detection side, thousands of rules were evaluated and distilled into a precision set of high-fidelity use cases - each MITRE-mapped across cloud, identity, endpoint, and network. This achieved 5X coverage velocity in under 30 days. Autonomous threat hunts ran continuously across every environment, proactively surfacing supply chain compromises, malicious container artifacts, and active extortion campaigns that never triggered a single conventional alert. Response time across investigation and resolution dropped to under 10 minutes, from a baseline of over 70.
Key Takeaways
What Security Teams Can Learn from Whatfix
Whatfix did not need a bigger SOC. It needed security to run where its team already made decisions. The results show what changes when the whole SecOps engine moves into the collaboration layer.
- Fewer, better detections. Thousands of untuned rules were distilled into a precision set of MITRE-mapped use cases, reaching 5X coverage velocity in under 30 days.
- Hunting that never stops. Autonomous hunts surfaced supply chain compromises, malicious container artifacts and extortion campaigns that never triggered a conventional alert.
- Response measured in minutes. Investigation and resolution time fell from more than 70 minutes to under 10.
- No console to check. Every finding, hunt result and response action arrives in Slack with full context, so the team never has to switch tools.
Read how Trench runs detection, investigation and response, see why teams choose headless SecOps, or explore the integrations, including Slack.