We build custom AI systems for SMBs that need them.

Layer 3 is connected data. Your AI stops working only in one tool at a time and starts pulling from your CRM, your spreadsheets, your transaction history, your customer feedback system, and your inventory data, combining them into a single analysis or report your team couldn't easily produce manually. A COO who gets a Monday morning briefing that synthesizes five data sources without touching a spreadsheet is using Layer 3. A feedback analyzer that decomposes customer ratings as a financial bridge is Layer 3. The data connections exist; what changes is whether the AI is doing the synthesis on demand.

Layer 4 is autonomous workflows. The system doesn't just answer questions or produce one-off reports. It runs on a schedule, monitors for conditions, makes decisions within defined rules, and escalates to a human only when it hits a case it was explicitly told it can't resolve alone. An email report that fires nightly, pulls live data, generates a narrative, and routes exceptions to the right person for review is a Layer 4 system. The distinction from Layer 3 is not sophistication. It's that nobody pushed a button.

Build engagements live in one or both of these layers. The class of problem they solve: multiple systems must coordinate, business logic is proprietary, failure modes have real cost, or the workflow needs to run autonomously in production without someone watching it.

Every Build system follows an orchestrator-doer pattern. The orchestrator receives the task, plans the steps, delegates to specialized sub-agents, and synthesizes the result. The doers are narrow: one pulls from the CRM, one queries the database, one generates the narrative, one routes the output. No single component is responsible for too much.

Human-in-the-loop gates are not optional add-ons. They are scoped into every system from the start. The question is where the human gate fires: before the system acts, after it produces a draft, or only when it hits an edge case it was explicitly told it cannot resolve. We design those gates before writing code, because retrofitting them after a system is live is much harder than building them in.

Error handling follows the same rule: every failure mode has a named behavior. Silent failures are not acceptable. If a data source is unavailable, the system says so and routes the exception. If a model output fails a validation check, the system retries with a tighter prompt or escalates. Nobody discovers three weeks later that a workflow has been silently returning blank results.

Build costs depend on many factors. Every engagement is custom-scoped during a 30-minute intake call. Fixed scope, fixed timeline, fixed price per engagement. What you pay is agreed before any work begins.

An optional maintenance retainer is available once the system is live. It is sold separately after launch, not bundled into the Build price. Not every client takes it. Some prefer to maintain the system internally after the handoff.