AI Studio
AI consultancy for complex problems that cut across teams, data sources and institutional knowledge.
We design and build custom AI systems for public institutions and foundations, for work that existing software does not cover, such as compliance casework, policy guidance and impact measurement. One team runs each engagement from scoping to adoption, and every system is built on the infrastructure that runs the Neol platform.
How our approach differs from a typical consultancy
A running system from the first week
Each build starts from the data, reasoning and deployment layers already in production on the Neol platform, rather than from a blank architecture.
Scope set by the institution’s mandate
The opening work agrees, with leadership, what the institution needs to change. The technical brief follows from that.
Accountable after launch
The team that built the system stays to support adoption and measure what changes, rather than handing over at go-live.
Start with the platform, or build around your own work.
Many clients do both: the platform runs their networks, and the Studio builds the systems around them.
Ready to deploy
Start with the platform
Your staff, alumni, partners and members become one network you can search, analyze and act on, configured for your organization and live in weeks.
Built for you
Build with AI Studio
We shape a system around your workflows, data and governance rules, and build it from the same components that run the platform.
Systems for the decisions an institution cannot afford to get wrong.
Each one works from records the institution already keeps, such as audit findings, policy documents and program data.
Compliance and enforcement
Audit findings, service records and public feedback become evidence-backed cases, with validation, service-level tracking and a clear path to escalation.
Knowledge and guidance
Policy, regulation and institutional knowledge become something people can ask, with answers that cite their sources, in more than one language.
Impact measurement and planning
Program, beneficiary and portfolio data come together as one evidence base, so impact can be measured and the next cycle planned on it.
Market and ecosystem intelligence
Operators, partners and markets are monitored and benchmarked, and what the data shows turns into targeted interventions.
Client story · A global government summit
A decade of summit content becomes a research tool leaders use every day
The challenge. Ten years of talks, panels and reports sat in spreadsheets, documents and video, tagged only by year, theme and title. Leaders had no way to trace how a debate had shifted, or to ground a new brief in what had already been said on stage.
The work. Neol structured the archive into a layer that understands context, then built research and comparison tools on top of it. A question such as how the conversation on AI governance has changed since 2018 now returns a grounded answer with exact references.
The outcome. An archive read once a year became a resource used day to day. Briefs, agendas and speeches now rest on precise evidence, and a decade of positions can be compared rather than remembered.
Strategy, design, engineering and adoption, in one team.
Ambitious AI work tends to stall in the handoffs: between the strategy and the build, and between the build and the people meant to use it. A Studio engagement has no handoffs. The team that frames the problem is the team that stays to see the system used.
Strategy
We define the problem, the scope and the architecture with your leadership before anything is built.
Domain expertise
Depth in government, talent and AI systems, so the difficult questions are asked early rather than discovered late.
Product design
Journeys and interfaces designed and tested with the people who will use the system every day.
Engineering
Full-stack and AI engineering: custom platforms, API layers and models trained on your data.
Delivery
Governance, milestones and hands-on support through go-live. We do not hand over a specification and leave.
Adoption
Launch is where the work starts to count. We stay to drive use, measure what changes and build on what works.
How an engagement runs
1 Define
We map the problem with your leadership team, agree the outcome that matters and design the architecture to reach it.
2 Design
Journeys and interfaces take shape with the people who will rely on the system, and are tested with them.
3 Build
Engineering starts from working components and is delivered against clear milestones through go-live.
4 Adopt
We stay after launch to drive use, measure what changes and extend what works.
Built on the infrastructure that runs the platform.
A Studio build starts from working components rather than from zero. It inherits the same data foundations, the same reasoning framework and the same deployment options as every Neol network.
Data enrichment
Records are cleaned, deduplicated and matched on several signals, with uncertain matches checked by people.
Profiles shaped for each use
Thin records become detailed, current ones, kept in sync with your own systems.
Reasoning built into the system
Parts of the reasoning are encoded in code and structured instructions, not left to a prompt.
Deployed where policy requires
In Neol’s cloud, in your own cloud tenant or on your own servers.
More ways to work with Neol.
Tell us about the problem, and we will tell you whether it needs the platform, a custom build or both.