FAQ

Yes. Our team is based in East Africa with strong links to Europe, and we work with clients and partners across borders, including in the US. We're set up for remote, cross-border delivery: clear communication, written decisions, structured project management, documentation, and direct access to the people doing the work.

For European clients, we pay particular attention to GDPR, hosting choices, data sovereignty, documentation, and handover.

We work especially well where information has to move clearly, systems need to be trusted, and delivery has real consequences. That often means digital and public health, operational and strategic insights, delivery and partnerships, climate and social impact, and UX research and product design.

We also take on adjacent projects with similar problems: sensitive data, complex workflows, reporting pressure, multiple stakeholders, compliance needs, or systems that have to keep working after launch.

Yes. We can support consultancies, agencies, NGOs, implementation partners, and specialist firms that need extra technical delivery capacity.

That can include software development, data engineering, dashboards, cloud infrastructure, AI integration, technical scoping, UX research, prototyping, implementation support, documentation, and handover. We can work visibly as Data XL or quietly behind the scenes, depending on the partnership.

Both. We design and build new software, data platforms, cloud infrastructure, and AI-enabled tools, and we stabilise, extend, modernise, or integrate systems that already exist. Many projects start with what's already there: improving an old application, connecting APIs, building a new reporting layer, or making a system easier to maintain, rather than starting from scratch.

We usually start by understanding the work the system needs to support: users, data, permissions, integrations, reporting, maintenance, and future growth.

Yes. We can help with product discovery, UX research, requirements gathering, workflow mapping, prototypes, technical scoping, and architecture. This is useful when an organisation knows it needs a digital system, but the exact product, workflow, or technical path is still unclear.

This can also support partners who have a client opportunity but need help turning it into a buildable plan.

Yes. We build dashboards, KPI frameworks, reporting flows, data quality checks, and decision-support tools. This can include management dashboards, financial dashboards, operational dashboards, programme dashboards, funder reports, and performance monitoring.

The goal is to help teams find the answer faster: what is working, what is slipping, where risk is increasing, and where action is needed.

Our AI work is designed around real workflows, data context, permissions, privacy, and governance. We build AI agents, AI-assisted dashboards, document extraction, classification, routing, summarisation, natural-language search, and AI features inside existing applications.

We also support private or European-hosted AI setups, where data isn't used to train provider models, isn't retained for provider learning, and doesn't leave the agreed environment.

Yes. We can design systems with GDPR-aware workflows: role-based access, data minimisation, retention logic, deletion workflows, data export, audit trails, consent or lawful-basis documentation, and clear view/access rights.

For us, GDPR belongs inside the system design. It affects how data is stored, accessed, shared, retained, exported, and removed.

Yes. We can help design systems where your organisation knows where data lives, who can access it, which providers are involved, and how data can be moved if a contract, provider, or system changes.

This can include EU-based hosting, private infrastructure, controlled cloud environments, role-based access, encryption, backups, and architectures that reduce unnecessary provider dependency.

Yes. We have experience with sensitive data in public health, operational, research, and organisational settings. We can design systems with privacy controls, access management, auditability, secure hosting, data separation, and careful documentation.

Sensitive data needs clear technical and operational boundaries from the beginning.

Projects usually start with a conversation about the work: what needs to happen, who will use the system, what data is involved, which systems already exist, what risks matter, and what would make the project useful.

From there, we can help with discovery, scoping, architecture, prototyping, implementation, or a phased delivery plan.

Yes. We can work alongside internal teams, IT departments, data teams, product teams, programme teams, or external partners. We can take responsibility for a defined delivery stream or support an existing team with specific expertise.

Clear roles, documentation, and communication are important when several teams are involved.

Yes. We can work inside your organisation's own development environment where that is preferred or required. That can include your GitHub organisation, GitLab, Bitbucket, internal code servers, ticketing systems, CI/CD pipelines, cloud accounts, VPNs, security policies, or other infrastructure used by your team.

This can be useful when code, data, credentials, or deployment access need to stay under your organisation's control.

Yes. Documentation and handover are part of serious delivery. Depending on the project, this can include architecture notes, data dictionaries, deployment documentation, user guidance, admin guidance, maintenance notes, and technical handover sessions.

Yes, where it makes sense. We can support maintenance, monitoring, bug fixing, improvements, reporting updates, data pipeline checks, cloud operations, or AI workflow tuning after launch.

The exact support model depends on the system and the client's internal capacity.