What we build
Six areas we build in.
Real work for real brands. These are not service lines off a menu — each one is a place we have built before and would build again, and none of them fits neatly inside a single discipline.
01
Healthcare
We build across health insurance and clinical technology: payer and member platforms, claims and benefits operations, the clinical systems care teams work in, and the data layer all of it depends on. This work sits where regulation, clinical reality and software meet, so a team that only understands the codebase will get it wrong.
Who we build it for
Health insurers and payer organizations, clinical software companies, and healthcare businesses building the systems their operations run on.
What we build here
- Payer and member-facing platforms
- Claims processing, adjudication and appeals
- Benefits configuration, eligibility and enrollment
- Clinical systems and the workflows that run inside them
- Provider network, credentialing and reference data
- Revenue operations, billing accuracy and reimbursement
- Healthcare data that has to be trustworthy before it is useful
- AI inside clinical and claims workflows, under human review
The team we put on it
- Insurance and payer operators
- Clinical systems specialists
- Product leaders
- Engineers
- Data professionals
- Claims and revenue specialists
- Regulatory and compliance advisors
What we can and cannot share
We never publish member or patient data, claims data, payer or provider names, product screenshots or contract terms. Protected health information stays inside the client's environment. Scope and context are shared under agreement.
02
Personalized marketing and market intelligence
We build systems that understand organizations and the people inside them, then act on that understanding. Closer to data and product engineering than to advertising — research, enrichment and messaging that hold up when a real buyer reads them.
Who we build it for
Personalized marketing platforms, revenue intelligence products and companies building their own go-to-market systems.
What we build here
- Organization and account research at useful depth
- Market intelligence that informs positioning, not just dashboards
- Data enrichment and the quality problems that come with it
- Persona-level research and segmentation
- Personalized messaging that survives human review
- Multichannel outreach and campaign execution
- Marketing automation and the systems underneath it
The team we put on it
- Growth and demand generation leaders
- Data and research specialists
- Product people
- Engineers working on data pipelines and enrichment
- Marketing operations specialists
- Content and messaging strategists
What we can and cannot share
Campaign performance, customer lists and proprietary data sources are not published. We describe the system, not the account.
03
Federal cybersecurity and certification readiness
We get technology, cloud infrastructure, products and operations ready to meet U.S. federal security requirements. This is readiness and implementation work. Eonexea is not an assessor and does not grant or issue any authorization or certification.
Who we build it for
Software and cloud companies pursuing federal work, and teams inside them carrying a security or compliance program.
What we build here
- FedRAMP Rev. 5 readiness and control implementation
- FedRAMP 20x preparation and the operational changes it implies
- Cloud security architecture and boundary definition
- Evidence, documentation and continuous monitoring practices
- Security engineering work that has to hold up under assessment
- Other federal security and certification requirements
The team we put on it
- Security architects
- Cloud and infrastructure engineers
- Compliance and GRC specialists
- Technical writers who can carry a control narrative
- Program leads who have been through an authorization process
What we can and cannot share
We do not name programs, agencies or sponsors, and we do not describe a company's security posture publicly. Nothing here should be read as a claim that a company is authorized.
04
AI and intelligent systems
We put AI into work that already carries consequences. The hard part is rarely the model — it is the workflow around it: what gets reviewed, what gets escalated, what a person is accountable for, and how the system behaves when it is wrong.
Who we build it for
Product companies embedding AI in what they sell, and operating businesses using it inside their own workflows.
What we build here
- AI-supported workflows with a clear review step
- Internal intelligence systems built on a company's own data
- Human-reviewed automation for work that cannot be fully handed over
- Decision support for people who are accountable for the decision
- Research and enrichment at a scale people cannot do by hand
- Operational AI inside existing business processes
The team we put on it
- Applied AI and machine learning engineers
- Product people who have shipped AI features to real users
- Data engineers
- Domain specialists who can judge whether an output is right
- Engineers working on evaluation and quality
What we can and cannot share
Model choices, prompts, evaluation results and internal data remain confidential. We describe the shape of the problem, not the implementation.
05
Product and engineering
We build the thing itself: a new product, the platform underneath it, or the internal systems a business runs on. It needs people who can hold product intent and technical detail at the same time, which is most of why we hire the way we do.
Who we build it for
Companies building a new product or standing up an engineering capability that did not exist before.
What we build here
- New digital products, from first version onward
- Internal platforms and the teams that depend on them
- Workflow systems that replace manual coordination
- Integrations between systems that were never designed to talk
- Data systems and business infrastructure
- Automation of work that does not need a person in the loop
- Product foundations that hold up as usage grows
The team we put on it
- Product managers
- Full-stack, backend and platform engineers
- Designers who work close to engineering
- Engineering leads
- QA and reliability specialists
What we can and cannot share
Roadmaps, architecture and unreleased product details are not published.
06
Data and automation
We take information spread across tools, inboxes and spreadsheets — with people spending their days moving it between them — and make it structured enough to operate, review and build on.
Who we build it for
Operating businesses and product companies where manual work has become the constraint.
What we build here
- Consolidating information that lives in too many places
- Data models that reflect how the business actually works
- Reporting people trust enough to act on
- Automating manual steps without losing the checks around them
- Migrations off tools a business has outgrown
- Operational systems that a non-technical team can run
The team we put on it
- Data engineers and analysts
- Automation and integration specialists
- Operations leads who can redesign a process, not just document it
- Analytics engineers
What we can and cannot share
Volumes, internal metrics and system diagrams belonging to a business are not shared.
A note on what is published here
Categories, not clients.
Some of what we build has not been announced. We do not publish names, product details or anything held in confidence.
If your work sits in one of these areas, or next to one, the fastest way to find out whether we can help is to describe the problem.
Looking for a specific role instead? Join Eonexea.