We re-architect mid-market departments into production agent systems — built on your stack, owned by your team, shipped in ninety days.
A boutique forward-deployed engineering practice. Two engagements per engineer at any time. We are the team that scopes the department, ships the production agent system, and gets paged when it fails.
Three weeks embedded with the team. We audit the workflow, build the eval rubric, and produce a written transformation blueprint that is yours whether or not we build.
A senior forward-deployed engineer ships the agent system — instrumented for evals from day one, deployed inside your cloud, your data warehouse, your existing systems of record.
Continuous evals, scope expansion, quarterly performance reviews. We are the team that gets paged when production fails, until you decide to take it in-house.
DAS-M, our Department-as-an-Agent-System methodology. Designed for ninety-day production deployment in mid-market environments — same shape across Finance, Revenue, and Logistics Ops. No deck-delivered transformations.
Two-to-three week paid Discovery Sprint. We embed with the team, audit the workflow, build the eval rubric.
Workflows mapped to agent architecture: tools, models, eval gates, human-in-the-loop, failure recovery.
A senior FDE writes the agent system, instruments it for evals from day one, deploys in your cloud.
Continuous evals, drift remediation, scope expansion, quarterly reviews. We get paged when it fails.
Each row below is an illustrative engagement — the kind of agent system we build in ninety days, calibrated to the systems and workflows of that industry. Read the case study for the engagement narrative; open the demo console to see what the system feels like running on synthetic-but-credible data.
Embedded with the finance team to map how work actually moves across AP, AR, close, treasury, and FP&A. Deployed across the existing ERP, expense, and reporting systems. No migration, no new software.
Mapped every handoff from lead intake through deal desk, forecasting, comp, and customer handoff. Deployed across the existing CRM, call recording, CLM, and enablement tools.
Mapped exception flows, demand planning, procurement, and warehouse coordination. Deployed across the existing ERP, WMS, and planning systems.
Why ninety-five percent of enterprise AI pilots fail to reach production — and how we prevent each named mode.
Ninety percent per step compounds to twelve percent end-to-end across twenty steps.
Evals from day one. Quantitative go-live gate.
Aggressive cost-cut deploy, quality drops, public walk-back, brand damage.
Co-design human-in-the-loop. Lock satisfaction floors.
A legacy API or undocumented data dependency blows the timeline by six weeks.
Tech due diligence first deliverable. Before pricing.
Production agents make a wrong call, no one can explain why, trust collapses.
Trace logging. Reasoning chains exposed.
A working POC, a thoughtful deck, a year of “scaling phase” with zero P&L impact.
Scope every engagement to production. Fixed go-live.
Thirty minutes. The founder runs every initial call. We will tell you in the first ten minutes whether StackLane is the right fit. If not, we will tell you who is.