Our work

Proof in real products.

We build software where AI has to do more than produce an impressive demo. It has to operate inside real workflows, integrate with application state, respect controls and remain useful once people depend on it.

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Two sides of AI-native engineering

Creative intelligence

Multimodal models, generation, editing and creative workflows.

Operational intelligence

Agents, policies, permissions, approvals and controlled execution.

Different products. Different risk models. The same product engineering discipline underneath.

Aurenza

AI-native agentic accounting platform

Agentic finance with governed execution.

Aurenza explores how specialized AI agents can reason, retrieve context and coordinate financial work while permissions, policies, approvals and deterministic accounting services remain in control of execution.

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What the product demonstrates

AI can participate in high-stakes workflows without becoming the final authority.

The engineering challenge is not only whether an agent can reason. It is how that reasoning interacts with application state, financial rules, permissions, approvals, evidence and irreversible actions.

Specialized AI agents

AI memory and context

Controlled tool execution

Permissions and policy gates

Approval workflows

Audit-ready evidence

Engineering lesson

AI where it creates leverage. Deterministic controls where correctness matters.

Streamling AI

AI creative production platform

Multimodal AI from first idea to finished media.

Streamling brings frontier image and video models, generation, editing, AI Director, Story Bible, avatars, audio, translation and creative workflows into one connected production environment.

The product challenge is not simply connecting model APIs. It is coordinating generation state, media assets, asynchronous work, editing tools and creative context so the experience behaves like one product.

Explore Streamling AI ↗

What the product demonstrates

Multiple models, media types and creative tools can still feel like one coherent product.

Frontier image and video models

Cinematic and animation workflows

Image and video editing

AI Director

Story Bible

Avatars, audio and translation

What connects the work

Two products. One engineering principle.

AI should become part of the product architecture — not a feature bolted onto the side. The exact architecture changes with the problem, risk and user experience.

AI belongs inside the product architecture

Models are most useful when they understand product context, permissions, workflow state and the tools available to them.

Different problems need different control models

Creative generation can tolerate exploration. Financial execution requires stricter rules, approvals, traceability and deterministic boundaries.

The product experience matters as much as the model

Useful AI software needs workflows, state, interfaces, queues, storage, failure handling and feedback — not only a model API.

Production changes the engineering problem

Reliability, cost, observability, permissions and maintainability become part of the design once real users depend on the system.

Client engineering

Product experience beyond our own platforms.

Our broader engineering background includes long-lived business applications, integrations, operational workflows and product modernization. Detailed client case studies should earn their place here with real scope, evidence and permission — not generic portfolio claims.

Our standard for a case study

Problem → constraints → delivered scope → engineering decisions → measurable or verifiable result.

Product modernization

Improving established software without forcing unnecessary rewrites.

Workflow & integration engineering

Connecting systems and turning manual operational handoffs into reliable software.

Business-critical applications

Engineering around permissions, data integrity, background processing and real operational constraints.

AI inside existing products

Adding useful AI capabilities while respecting the architecture and controls already supporting the business.

Our standard

Show the engineering, not just the screenshot.

A polished interface does not explain whether the architecture was difficult, the workflow became more reliable, the system integrated correctly or the release produced useful results.

As we publish client case studies, we want them to explain what was constrained, what changed, why particular engineering decisions were made and what evidence supports the result.

Evidence over adjectives.

Start with one outcome

What should your product deliver next?

Tell us what your product needs to do next — a new capability, AI initiative, workflow, integration or modernization effort. We’ll help define the smallest sensible way to move it forward.

Bring us

A releaseAn integrationA workflowAn AI initiative

Discuss your roadmap

Focused conversation. No long sales process.

01 Move quickly

02 Stay adaptable

03 Engineer carefully

04 Ship with confidence