Real teams. Real results.
See how companies across industries use Wonka to hire faster, screen smarter, and build stronger teams.
How DPC Found the Right People to Care for Dubai's Dogs
attrition (first 90 days)
confirmed shortlist
confident in interviews
screening calls
"We care deeply about every animal that comes through our doors, and that means we need people who share that standard. Wonka helped us see who those people actually are before we ever meet them. The shortlist it gives us is genuinely useful — not just a stack of CVs."
Ruslan Kaimov — Head Trainer, Dog Performance CenterThe Challenge: Hiring for Skill and Heart in a Specialist Field
At Dog Performance Center, quality isn't a nice-to-have — it's the whole business. DPC provides elite training, grooming, and care services for dogs in Dubai, working with clients who hold exceptionally high expectations for how their animals are treated. Every member of the team, from senior trainers to front-of-house staff, needs to combine genuine animal handling knowledge with the patience, temperament, and professionalism the role demands.
That's a hard combination to find. And harder still to assess from a CV.
DPC's hiring process had long relied on interviews and gut instinct. But the cost of getting it wrong was steep — a trainer who couldn't read animal body language, or a groomer who struggled under pressure, affected not just the business but the animals in their care. The team was investing hours in candidates who cleared the interview stage but revealed knowledge gaps or attitude problems once on the floor.
The challenge wasn't finding applicants. Dubai's diverse, international workforce means DPC regularly receives strong volumes of interest. The challenge was filtering confidently — identifying, early in the process, which candidates had the right knowledge, the right mindset, and the communication skills to work with both animals and clients at DPC's level.
The Solution: Assessments Built for the Real Job
DPC partnered with Wonka to redesign their screening process from the ground up, building assessments that reflected the actual demands of each role.
For trainer and handler positions, Wonka assessments combine multiple-choice questions on animal behaviour and handling techniques with open-text responses that ask candidates to describe how they'd approach real scenarios — an anxious dog during a session, a difficult conversation with a concerned owner. These responses reveal not just knowledge, but judgment and communication style in one step.
For grooming and veterinary support roles, assessments test technical awareness and safety knowledge, filtering out candidates who lack foundational skills before any face-to-face time is invested.
Across all roles, video responses give DPC's team a window into how candidates present themselves — their energy, their warmth, their professionalism. In a business built on trust between staff, animals, and clients, how someone comes across matters as much as what they know.
Once assessments are live, Wonka generates a unique application link that DPC includes in every job posting and outreach message. Candidates complete at their own pace. When DPC's hiring team logs in, they find a ranked shortlist with scores and key insights for each candidate — the information they need to decide who's worth a conversation, presented clearly and without noise.
Why It Works for Specialist Service Teams
DPC's experience points to something broader about hiring in high-care, specialist environments. When the wrong hire isn't just a performance issue but a welfare and reputational risk, screening needs to do more than filter on experience. It needs to assess judgment, attitude, and communication — the things that don't show up on a resume.
Wonka's flexible assessment formats — video, open text, scenario-based questions — let DPC ask the questions that matter most to their business, not just the ones that are easy to score. The result is a shortlist that reflects who candidates really are.
How Finazon Hires the Rare Talent Their Data Platform Demands
final-round interviews
early screening
posting to shortlist
at 3-month review
"The candidates we used to lose hours screening out — Wonka catches them immediately. And the ones who score well on the assessment? They almost always live up to it. That kind of signal is genuinely hard to find when you're hiring for such a specific profile."
Yury Sokolov — CEO, FinazonThe Challenge: A Narrow Target in a Crowded Market
Finazon aggregates financial data from hundreds of sources — stocks, forex, crypto, economic indicators — and delivers it to developers and institutions via API. It's a technically complex product serving a technically demanding customer base. The people who build and support it need to speak both languages: the language of software engineering and the language of financial markets.
That's a narrow profile. And finding it is harder than it sounds.
When Finazon opened roles, they'd attract plenty of strong engineers who'd never worked near financial data, and plenty of finance professionals who couldn't engage with the technical depth the role required. Both types looked credible on a CV. Both types consumed interview time before the gap became clear. The team — lean by design, with no dedicated recruiting function — couldn't afford that kind of churn through the top of the funnel.
There was a secondary challenge too. Finazon's customer success and support roles sit at the same intersection. Clients are developers and quants who expect precise, knowledgeable answers. Hiring someone warm but technically shallow in those roles meant problems downstream — escalations, churn, trust eroded with exactly the customers Finazon most needed to retain.
The Solution: Dual-Track Assessments that Mirror the Real Role
Finazon worked with Wonka to design assessments that tested the specific combination of skills each role required — before anyone picked up the phone.
For engineering roles, assessments include coding challenges grounded in real financial data contexts: working with time series, handling high-frequency updates, structuring API responses. These aren't abstract exercises — they reflect exactly what candidates will do on day one. Paired with open-text questions on data architecture decisions, the assessment quickly separates engineers who can navigate financial data environments from those who'd need a long ramp to get there.
For customer-facing roles, Wonka assessments combine technical multiple-choice questions — testing knowledge of market data concepts, API usage, and data formats — with video responses where candidates explain complex ideas clearly and calmly. It's a direct proxy for what the job actually looks like.
Finazon generates a Wonka application link for each opening and routes all applicants through it, regardless of source. Within days, they receive a ranked shortlist with individual scores and insights — a clear view of who has the right profile, not just a strong resume.
Why It Works for Niche Technical Teams
Finazon's challenge is common in specialist data businesses: the ideal candidate exists at the intersection of two demanding disciplines, and generic screening tools — or gut-feel interviews — aren't precise enough to find them reliably.
Wonka's flexibility to build custom assessments around the exact knowledge and skills a role requires is what makes the difference. For teams without a dedicated recruiter, it effectively acts as one — running the same rigorous, tailored screening process for every candidate, every time, without adding headcount.
How Twelve Data Builds a World-Class Remote Team — Without the Screening Bottleneck
interview
per open role
early-stage screening
exceeds" at 6 months
"Before Wonka, our hiring process couldn't keep up with how fast we were growing. We'd get great candidates who went cold while we were still trying to schedule screening calls. Now we have a shortlist ready within days of opening a role — and we actually trust it."
Den Armstrong — Twelve DataThe Challenge: Scaling a Remote-First Tech Team at Speed
Twelve Data powers financial applications around the world. Their market data APIs give developers real-time access to stocks, forex, crypto, and over 100 technical indicators — and demand for their platform has grown fast.
With that growth came a hiring challenge. Twelve Data operates as a remote-first company, drawing talent from dozens of countries. That's a competitive advantage when it comes to access to skills. But it creates a real screening problem.
When a role opens at Twelve Data, hundreds of applicants can come in from across the globe, spanning every time zone. Scheduling live calls to screen even a fraction of them was eating into the team's time. Their small recruiting function was stretched thin, and hiring managers — engineers and technical leads who had other work to do — were being pulled into first-round calls that could have been filtered much earlier in the process.
The deeper issue wasn't just time. It was consistency. Different interviewers asked different questions. Evaluations were subjective. It was hard to compare a strong communicator in one timezone against a strong technician in another — especially when those conversations were weeks apart.
The Solution: Structured Assessments, AI-Ranked Shortlists
Twelve Data turned to Wonka to bring structure and intelligence to their screening process.
They set up role-specific assessment tracks directly inside the Wonka platform, tailoring each one to the demands of the position. For engineering roles, candidates complete coding challenges — practical problems that reflect the kind of work they'd actually do at Twelve Data. For analyst and support positions, assessments combine multiple-choice questions on technical knowledge with open-text responses that reveal how candidates think through problems. Video responses are used across all tracks to evaluate communication clarity, which matters deeply in an async, remote environment.
Once a role goes live, Wonka generates a unique application link. Twelve Data shares it in job postings, emails, and on their careers page. Candidates complete the assessment on their own schedule — no coordination required, no scheduling overhead. The experience is the same whether a candidate is in Berlin, Nairobi, or Singapore.
Behind the scenes, Wonka's AI evaluates each submission across multiple dimensions: technical accuracy, response quality, communication skills, and role-fit signals. Every candidate receives a score. Every shortlist arrives ranked, with individual insights that show exactly why a candidate placed where they did.
Why It Works for Remote-First Teams
For a company like Twelve Data, the asynchronous nature of Wonka is as valuable as the AI ranking itself. Candidates aren't penalized for being in a difficult timezone. Hiring managers aren't sacrificing engineering time to run first-round calls. And the evaluation criteria stay consistent across every candidate, every role, every region.
Wonka doesn't just speed up screening. It makes remote hiring fairer — and a lot less stressful.
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