Wally, Director of IT at CookUnity, faced a challenge that would make most IT professionals break into a cold sweat: supporting 1,000 employees across corporate offices and field operations with a team of just two people. That's a staggering 500:1 ratio—five times the industry standard.

When Wally arrived at CookUnity, the IT help desk was already using Atlassian Assist integrated with Slack. Users were submitting questions, but that's where the good news ended. Requests weren't being routed or sorted correctly, first responses were delayed, and people were left wondering about their ticket status. For a company that operates 24/7 food production facilities, this wasn't just inconvenient—it was a business risk.

The Challenge: An Unsorted Pile with No Visibility

The fundamental problem was simple but severe: everything came into one giant pile.

"Everything came into a pile," Wally explained. "No segmentation, no priority given to different things. IT has to sort through the pile and decide what is important, what needs to happen, what's time sensitive."

The lack of searchability made things worse. Tickets would get lost. If someone needed to find a previous issue about "the Hoboken printer," searching for it in Jira wouldn't surface the relevant ticket. The team was flying blind.

But there was another problem eating away at their bandwidth: repetitive questions. The same questions were coming in 3-4 times a day—requests for Tableau access, WiFi passwords, software managed by other teams. Each one required manual attention, counted against SLA metrics, and all the agent could do was say "IT doesn't manage this, please reach out to this channel" before manually closing the ticket.

With an 8-hour average first response time and a 72-hour resolution time, it was clear something had to change.

The Solution: Intelligent Routing and AI Deflections

Wally had used Foqal at a previous company, so when he assessed the situation at CookUnity, he knew what was possible. After demoing the platform's newer features—particularly AI auto-resolutions—he made the switch in January.

The transformation came from two key capabilities:

1. Intelligent Segmentation and Routing

Foqal allowed the team to segment tickets by type and create separate queues for field operations versus corporate operations With proper segmentation, the team could prioritize revenue-impacting issues and ensure nothing slipped through the cracks.

An 8-hour reminder automation nudged agents if any ticket went unanswered, ensuring every request got attention.

2. AI Deflections for Repetitive Questions

Beyond the sorting problem, a significant portion of incoming tickets were questions IT couldn't actually help with—Tableau access requests, WiFi passwords, and software managed by other departments. Each ticket still had to be opened, read, responded to with a redirect, and manually closed. At 3-4 per day, these were eating hours every week while counting against SLA metrics.

Foqal's AI deflections solved this by connecting to CookUnity's Notion knowledge base. Now when someone requests Tableau access, the AI responds in 30 seconds: "Tableau is handled by the data team. Please request this in #data-help." It then asks if that answered their question. Yes means the ticket auto-closes. No means IT gets notified.

The result: 3-4 fewer manual interventions per day, freeing the team to focus on problems that actually require their expertise. For an already-understaffed team, that recovered time makes the difference between reactive firefighting and proactive support.

The Second Challenge: No Data to Justify Resources

Beyond the operational chaos, there was a strategic problem: without metrics, Wally couldn't justify headcount or even plan an annual budget. How many computer upgrades happened last year? How many field operations requests came from which budget? He had no idea.

At CookUnity, like most companies, headcount approvals require data. Going into OKR meetings with vibes instead of numbers meant starting every conversation at a disadvantage.

Data-Driven Decisions and Headcount Approval

Foqal's dashboards solved this immediately. Wally could now show leadership concrete numbers: ticket volume, resolution times, request types, segmentation by department.

The data told a clear story. Of 808 tickets, 217 were software access requests—questions his team couldn't even answer. This insight led to creating a system index in Notion that Foqal could reference for future deflections.

More critically, the numbers proved the team was doing two jobs: corporate IT and field operations support. With that evidence, Wally secured approval for an additional IT role.

The Results: 50% Faster Response, 70% Faster Resolution

Since implementing Foqal in January:

• First Response Time: 8 hours → 4 hours 7 minutes (**50% **improvement)
• Time to Resolution: 72 hours → 21 hours (70**% **improvement)
• Tickets Deflected: 3-4 per day handled automatically
• Visibility: Complete segmentation revealing 54 weekly field operations requests that were previously invisible
• Headcount: Additional IT role approved based on dashboard data

Beyond IT: Foqal Spreads Across Teams

The strongest validation came when other teams asked to use Foqal too.

The infrastructure and DevOps team saw IT's setup and wanted the same capabilities. They got their own channel and workflows.

CookUnity's procurement manager built an approval workflow for field equipment requests—industrial printers, scanners, and other tools. Budget owners now approve or deny purchases directly in the workflow, no manual coordination needed.

Why Foqal?

Wally's advice: get a demo and start building.

The difference from traditional tools was stark. Transparent pricing, honest feature demos, responsive support available for screen shares. Compare that to tools like Jira, where remembering how to do everything requires a dedicated employee.

The Bottom Line

CookUnity's two-person IT team went from drowning in an unsorted pile to running a data-driven operation. Response times cut in half. Resolution times down two-thirds. Hours recovered every week through automation.

But the real win was visibility. That visibility became organizational support: a new headcount, better processes, and recognition of IT's strategic value.

For a team supporting 1,000 employees, these improvements aren't nice to have. They're the difference between surviving and thriving.