Careers at Catapult

Claude and OpenAI are building increasingly intelligent general models. We are solving a different problem: giving AI a deep, persistent understanding of your work.

Their connectors and MCPs retrieve a few emails, messages or documents after you ask a question. Catapult already understands how those conversations, people, projects and decisions connect, and keeps that understanding current as your work changes.

Models will keep improving and we can use whichever one is best. Our advantage compounds separately: a living model of you, your company and how work actually gets done. Better intelligence helps everyone. Better context makes Catapult better for our users.

In our internal tests, Catapult outperforms the highest-tier models in Claude Cowork and ChatGPT Work on most knowledge work tasks. Examples include:

• Answering complex questions across your work by tracking down the data, decisions and history scattered across meetings, messages, documents and tools.
• Drafting emails in your voice after reading the whole thread, understanding the relationship and checking every promise still outstanding.
• Creating social posts from work you had forgotten about, finding the strongest product progress, customer proof, conversations and lessons before writing them in your voice.
• Turning meetings into next steps by working through what was decided, updating the plans and drafting every follow-up people promised.
• Building board packs and investor updates by pulling together the latest financials, company metrics, progress, risks and commitments from previous meetings.
• Spotting which leads to contact after every release, matching what shipped to what each person previously asked for and drafting the messages.
• Drafting PRDs after reading the codebase, listening to user calls and tracing the decisions that shaped the product.
• Preparing you for customer meetings by remembering the full relationship, what each person cares about, what you promised and what remains unresolved.
• Drafting proposals and statements of work by turning customer conversations, pricing, product capabilities and implementation requirements into a finished document.
• Completing RFPs, RFIs and due diligence by finding the latest answers from across the company and filling in every spreadsheet and document.
• Answering questions about company performance by finding the right numbers, checking where they came from and explaining what changed.
• Creating tickets for recurring problems by pulling together the user reports, internal conversations and evidence engineers need to ship the fix.
• Updating the sales pipeline from what actually happened across meetings, emails, proposals, product usage and promised next steps.
• Turning recurring customer feedback into product priorities by finding the patterns across calls, support threads, usage data and internal conversations.
• Finding commitments that are about to be dropped, working out who is waiting on what and drafting the messages needed to close each loop.
• Planning renewals and expansions by bringing together product usage, customer requests, support history and recently shipped features.
• Working out why a project is late by retracing the original plan, changed requirements, dependencies, blockers and decisions behind it.
• Bringing new joiners up to speed on the product, its history, why decisions were made, who owns what and how work actually gets done.
• Writing stand-ups, performance reviews and progress updates from the work people actually did, including contributions nobody remembered to record.
• Completing security questionnaires by finding current answers across your architecture, policies, controls, vendor records and previous responses.
• Evaluating candidates by reading the job spec, CV, application, interview history and how you assessed similar candidates.
• Updating financial models with actuals and new assumptions, preserving the formulas and showing you exactly what changed.
• And many more.

Real work is messy. A single decision might begin in a meeting, continue in Slack, appear in an email and eventually change a document or customer plan.

Catapult must understand those connections across millions of pieces of information, keep that understanding current, respect permissions and reliably select the right context for each task. We are also solving evaluation, safety, document understanding and agent execution across wildly different customer environments.

Our typical process is:

1. A founder interview focused on your background, ambition and how you think.
2. A follow-up conversation about problem-solving and judgment.
3. A deeper session where you present something you know exceptionally well and work through a real Catapult problem on a whiteboard.
4. A paid work trial in our office.
5. References & offer extended.

We do not rely on generic coding tests. We care more about how you reason, communicate and work on a difficult problem with the team.

Yes. We sponsor visas for exceptional people and already have the infrastructure to do it.

We care about finding the best person, not where they were born or which passport they hold. If there is a strong mutual fit, we will work with you on the appropriate UK visa route and cover the company side of the process.

We offer competitive salaries and meaningful stock options because we want everyone at Catapult to share in the upside they help create.

Our UK benefits include:

• Bupa private healthcare
• A wellbeing allowance
• A tax-efficient pension scheme
• 34 days of paid holiday, including public holidays
• A workplace nursery benefit
• All the equipment you need to do your best work

You'll contribute from day one and take ownership of meaningful problems within your first month, turning them into something users rely on. Expect direct support, fast feedback and broad responsibility, not layers of management or a narrow box.