How ivee scraped 50 job boards and tripled their job listings with Gaffa
Read how ivee used Gaffa to scrape 50 job boards, tripling their curated job listings and saving 10 hours of manual work per week.
Feb 13, 2026
ivee is a small, mission-focused startup helping people stay competitive amid AI job shifts. A core part of their offering is a vetted platform for job listings – but building and maintaining that list was entirely manual. They needed a scalable, reliable way to scrape listings, but lacked the development resources and scraping experience to handle it internally.
With Gaffa, ivee scraped more than 50 company job boards across 5 different applicant tracking systems, tripling the number of curated listings they could show. Their job board now displays salary information, benefits, and more, all with little to no manual work. As ivee adds new boards, closed listings are automatically removed, keeping users working from up-to-date information.
And it all came together on a tight turnaround – ivee needed the data ready before their appearance on Dragon's Den (Shark Tank for US readers), where they knew they'd face a massive surge in new users.
Manual processing doesn't scale
ivee provides users with micro-upskilling based on real-time market data, plus access to vetted job listings from employers looking for AI-fluent talent. Until recently, filling their platform with listings was entirely manual – the team was hand-processing job data from company career pages, copying across titles, salaries, benefits, and descriptions one listing at a time. Building integrations with the various applicant tracking systems (ATSs) that power these job boards required development resources they didn't have.
As a result, the ivee team was always wary of breaking user trust. If listings were too limited, users would turn to other job boards; if listings were out of date, users would click through and be disappointed to find a seemingly open job was closed.
This created a crunch: ivee had to add as many vetted jobs as possible and manually monitor listings after they were posted to ensure they were still open. Between two team members, this ate up 10 hours every week – time spent on repetitive data processing instead of growth. This crunch intensified as the team prepared to go on Dragon's Den.
How ivee scaled their data extraction with Gaffa
When ivee found Gaffa, the fit was clear. With Gaffa, organisations can scrape and automate browsers without needing frameworks, proxies, headless browsers, or complex configurations – all through a REST API, making it easy to integrate with other tools. No SDK or plugin needed.
The ivee team worked with Gaffa to build a scraping management dashboard in Retool. Now, as the team adds new job boards, Gaffa automatically scrapes the listings and adds them to the job manager app.
Scraped information includes:
- Job title
- Working structure
- Location
- Description
- Benefits
- Salary range
Gaffa features like generating markdown, using AI to extract unstructured data as JSON, and capturing the raw DOM of the page were all used to simplify data extraction. Developers without scraping experience can easily maintain the application, and non-technical team members can use it effectively.
As Lara Kennedy, Head of Consumer Marketing at ivee, says:
The scraping dashboard powered by Gaffa was one of the easiest tools to get to grips with, and I'm saying that as a non-technical user.
Lara Kennedy
Head of Consumer Marketing @ ivee
What makes Gaffa different
There are plenty of scraping tools, but Gaffa enables every developer to become a scraping expert by handling the complexity for them. Here's what that looks like in practice.
1. Gaffa turns complexity into simplicity
Job boards seem simple at first glance, but extracting standard data from them is deceptively complex.
Companies typically use Applicant Tracking Systems (ATSs) to populate job boards, and companies using the same ATS often have different styles and formats. Within a single company, different teams submit listings, so formats are rarely standardised. Some companies self-host their boards entirely, requiring different extraction techniques.
Gaffa Browser Requests handle the most complex situations as effectively as the simplest.
For a simple job board where each listing is a separate page with its own URL, Gaffa can extract information without issue.
For more complex boards with multiple pages and non-unique listing URLs, Gaffa can loop through each page, find the next button, click it if available, and capture HTML files as it goes – all until no more pages are found. Throughout, Browser Requests also manage proxies, ensuring scraping without getting blocked.
Fetching job listings from a multi-page board
Most scraping frameworks would require specialised scripts for every kind of site – not so with Gaffa. The complex scenarios become as simple as the straightforward ones.
2. Gaffa parses the most relevant information
Gaffa uses LLMs to give you more than just a raw web page. The Parse JSON action extracts structured data from web pages using AI to parse content into predefined data schemas, returning results as a JSON object. Once the content is in JSON format, it can be easily used in automations, analyses, and more.
With other solutions, you often need to create data pipelines or parse the code yourself. Even when other solutions provide AI, you still often need to check its work to ensure the returned schema exactly matches the format you provided.
Gaffa offers full control over how you use the LLM, including the ability to hone a prompt with descriptions and titles, focus parsing on specific elements, and even change the model. The focus feature allows teams to use smaller, cheaper models because they don't have to parse known irrelevant information.
With Gaffa, LLM inputs are focused and relevant, producing inexpensive, accurate results.
3. Gaffa saves development resources
Adding more job boards used to mean more manual effort to keep up with. With Gaffa, as the team adds boards, the monitoring work stays the same: zero. Jobs in the "live" category automatically disappear when the company board closes them. No one needs to manually check whether listings are still open.
The ivee team doesn't need to build data pipelines, queues, or job management systems. Gaffa's API handles multiple concurrent requests, failures, proxies, AI parsing, and markdown generation. And because it's a REST API, it integrates into almost any development environment.
The 10 hours per week that two team members previously spent on manual data processing is now entirely automated. Lara can spend her time on learning and deploying new AI business tools, strategic thinking, and creative campaigns. As she puts it, the work has shifted from manual drudgery to "spending time on growth."
"We review the job data on a weekly basis, using AI agents to assist us," Lara says. "As we are such a small team, the ability to access this data and insights so quickly is a massive time-saver."
Knowing we now have the infrastructure set up for the future is incredibly comforting, especially as an early-stage start-up that is constantly evolving. The number of people complaining about closed jobs has pretty much reduced to zero
Lara Kennedy
Head of Consumer Marketing @ ivee
Adding 650 listings just in time for a surge in traffic
With Gaffa, ivee went from manually processing job data 10 hours a week to fully automated scraping across 50 boards. They tripled their curated listings to 850 – their highest ever. When they appeared on BBC's Dragon's Den and received an 80,000% surge in traffic, every one of those listings was accurate and up-to-date.
"The number of people complaining about closed jobs has pretty much reduced to zero," Lara says. "It saves our customer service a lot of time, sanity, and leaves a more positive impression of our site amongst users."
Try Gaffa today
Gaffa is a simple REST API that enables organisations to automate browsers in minutes. Whether your use case is scraping, printing web pages, taking screenshots, or converting pages to LLM-ready markdown, Gaffa can turn manual pain into automated growth. All with a single API call.
The ivee team used a range of features you can read more about in our docs, including:
When these features come together, ivee could use Gaffa to scrape the careers page list, get the DOM, extract the jobs list, get the job info and markdown description, and parse data into JSON. With Gaffa, ivee doesn’t need to pore through job listings by hand again.
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