Services
Most projects combine more than one area. We start with the workflow and the people doing it, then decide what to build.
Customer portals, internal tools, and line-of-business applications shaped by the workflow they support.
Analytiq, a self-hosted analytics workspace, a multi-user project workspace, and Mesob's restaurant operations layer.
Practical AI features that fit an existing workflow: assistants, retrieval, document processing, agents, and the evaluation needed to trust them.
Cue, an open-source real-time copilot, and Analytiq's AI chat interface.
Wallet, payment, and card software where balances, transaction state, and reconciliation have to be correct.
Velox, a virtual card wallet architecture with a ledger, FX conversion, and card-issuing integration.
Software for farms and agricultural teams: production records, inventory, deliveries, customer billing, and the mobile workflows used in the field.
Dairy, a farm operations system covering herd records, milk production, deliveries, billing, and payments.
APIs, data models, and integrations that let separate systems exchange information without fragile manual work.
NodeStack, a tenant-aware service architecture with authentication, audit logging, and notifications.
Practical training for teams that need to use AI well: model selection, prompting, tool use, evaluation, data handling, and internal guidelines.
Sessions delivered around a team's current tools and workflows, with working examples.
How an engagement works
Each stage produces something you can review: a defined problem, an agreed scope, a working release, and a supported handover.
We start with the workflow, the people, and the constraints. You get a written understanding of the problem before scope or design is proposed.
We define the data, roles, edge cases, and smallest useful release. You approve the scope before build starts.
We work in short increments and share working software as it takes shape. Decisions are made against the product, not a document.
We hand over a documented system and stay available for fixes, maintenance, and improvements. Support terms are agreed before launch.
Common questions
If your question is not here, send it directly. We would rather answer honestly than promise a fit that is not there.
Ask a questionWe work on applications, operations systems, AI features, fintech software, agriculture software, APIs, and AI training. We take on work where there is a clear operational problem and a team that wants software built around how the work happens.
Yes. We build assistants, retrieval and document workflows, automation, and AI features inside existing products. We also help teams evaluate models, handle failures, control cost, and decide where AI should not be used.
Yes. Our related work includes Velox, a virtual card wallet architecture, and Dairy, a farm operations system for herd records, production, deliveries, billing, and payments. We are careful about regulated claims and will be direct about what we can verify.
Yes. We run practical sessions around a team's current tools and workflows. The goal is not a generic AI overview; it is a shared standard for prompting, review, data handling, evaluation, and when a person must stay in the loop.
Yes. We start with a review of the current architecture, constraints, and delivery history. If the right move is to stabilize and improve what exists, we will say so. If a rebuild is justified, we will explain why.
We define scope first, then agree on a fixed-scope engagement or an ongoing arrangement. We do not publish a rate card because the shape of the work varies. Tell us the problem, the constraints, and the timeline, and we will be direct about fit.
Yes. We can hand over a documented system, remain available for fixes, or take on ongoing maintenance and improvement. The arrangement is agreed before launch so there is no ambiguity about what comes next.
Start a conversation
A short description of the workflow, the people involved, and the constraint that matters most is enough to start.