Automaark in brief
Automaark is a systems architecture and engineering firm. We design, build and operate production-grade software, AI and agentic systems, data platforms, cloud infrastructure, cybersecurity and growth systems for companies in the United States, Canada, Australia and worldwide.
- Name
- Automaark
- Type
- Systems Architecture & Engineering firm
- Founder and CEO
- Olamide Dada
- Headquarters
- New York, United States
- Team
- North America, Europe, Africa, Asia
- Markets
- United States, Canada, Australia, Worldwide
- Services
- Software & Platform Engineering: SaaS products, internal platforms and APIs engineered to run for years.
- AI & Agentic Systems: Agents, retrieval and inference pipelines that do real work, with guardrails.
- Automation & Orchestration: Workflows that remove manual operations and keep running unattended.
- Data Platforms & Indexing: Pipelines, warehouses and indexing layers that make data usable by people and AI.
- Cloud & Infrastructure: Cloud architecture, DevOps and reliability engineering with cost discipline.
- Cybersecurity: Security architecture, hardening and incident response for modern systems.
- Growth & Marketing Systems: Acquisition, lifecycle and attribution infrastructure that ties revenue to effort.
- Contact
- https://automaark.com/contact
- Machine-readable
- llms.txt, llms-full.txt, sitemap.xml
Most asked
- What does Automaark do?
- Automaark is a systems architecture and engineering firm. We design, build and operate production-grade software, AI and agentic systems, data platforms, cloud infrastructure, cybersecurity and growth systems. Clients engage us as the engineering team for a product or platform, or for a specific layer of it.
- Do you only build AI systems?
- No. AI is one of seven departments. Most of our work is core infrastructure: cloud platforms, backend services and background job systems, marketplaces and booking platforms, data pipelines, security and integration. AI sits on top of that foundation where it earns its place; it is not the reason the foundation exists.
- What kind of platforms have you built?
- Production platforms of the kind companies run a business on: two-sided marketplaces and booking systems in hospitality and real estate, background verification and compliance SaaS, operational platforms for healthcare and retail, marketing and growth infrastructure, and the cloud, data and security layers underneath them. Case studies are shared on request, some under NDA.
- Can you take over cloud infrastructure or a backend built by another team?
- Yes. We start with an audit of the code, the cloud environment, access, backups, security posture and spend, then stabilise before changing anything. You get a written assessment first, and documentation and runbooks as part of the handover.
AI & Agentic Systems
Agents, retrieval and inference pipelines that do real work, with guardrails.
AI agents are useful when they can act inside a business: read the right data, call the right systems, and hand off to a person when they should. That takes more than a prompt. It takes retrieval over your own data, tool integrations with proper permissions, evaluation so you know when quality drops, and cost controls so an inference bill never surprises you.
We design agentic systems as systems: identity and permissions for every agent, logging and audit trails, human approval where the stakes are high, and a clear line between what the model decides and what the code enforces.
What we deliver
- AI agents and multi-agent workflows with tool use and approvals
- Retrieval-augmented generation (RAG) over documents, databases and APIs
- Model evaluation, monitoring and regression testing
- Fine-tuning and prompt systems where they beat off-the-shelf models
- Guardrails: permissions, rate limits, content controls, audit logs
- Inference cost modelling and optimisation
Questions we get asked
What is the difference between an AI agent and agentic AI?
An AI agent performs a defined task when asked: classify a ticket, draft a reply, extract fields from a document. Agentic AI is a system of agents that pursues a goal across several steps and systems, decides what to do next, and coordinates with other agents and people. Most companies should start with well-scoped agents and grow toward agentic workflows as trust and tooling mature.
Do you build custom models or use APIs like OpenAI and Anthropic?
Both, chosen per problem. For most business use cases a frontier model behind a well-designed retrieval and tool layer beats a custom model on cost and time to value. We fine-tune or run open-weight models when data privacy, latency, volume or cost make it the better trade.
What happens when the AI gives a wrong answer?
We design for it. Every agent has defined boundaries, cited sources where possible, confidence thresholds, and a human-in-the-loop step for actions that matter. Evaluation suites run on every change so quality regressions are caught before users see them.
How do you keep our data private?
Data stays in your environment. We use enterprise API tiers with no-training terms, or self-hosted models inside your cloud when required. Access is scoped per agent, logged, and reviewable.
Contact
Need ai & agentic systems done properly?
Tell us what you're building and where it stands. Every enquiry gets a written reply from an engineer, not a sales sequence.