Software and AI that hold up in production.
SBL helps CTOs, product leaders and operations teams design, build and run business-critical software, AI workflows and data platforms, from architecture to launch to long-term support.
SBL helps CTOs, product leaders and operations teams design, build and run business-critical software, AI workflows and data platforms, from architecture to launch to long-term support.
Companies don't struggle because they lack software.
They struggle because their tools don't fit the way decisions move, data changes and people get work done.
We build software, AI workflows and data systems around the people, processes and constraints that run the business.
AI and software projects fail when strategy, engineering and operations sit with different owners. We keep them together.
AI only creates value when it changes how work gets done. That's why we build the workflow, controls and integrations around it.
Plan an AI or software build →Actigen provides the workflow, governance, integration and operational foundations behind AI systems so teams can focus on solving business problems instead of rebuilding infrastructure.
Actigen brings together ingestion, orchestration, governance and user workflows in a reusable foundation built for production environments. Deploy it within the cloud, security and compliance model your team already trusts.
Search, extract and govern large document collections.
Automate reviews, reporting and customer workflows.
Support clinical, payer and operational workflows.
Track assets, field operations and sustainability data.
Connect quality, maintenance and production systems.
Support learning, enrollment and student operations.
The industry changes. The operational problems rarely do: fragmented data, manual workflows and systems that don't fit the way people work.
4,000+ projects delivered across regulated, operationally complex industries.
Most software problems aren't technical problems. They're decisions that were never made. We surface the tradeoffs early: scope, data quality, security, adoption and ownership. That keeps them from turning into delays and rework.
Most software failures can be traced back to decisions made too late. Our process is designed to surface them early.
We map how work actually happens: people, data, approvals and failure points. The goal is to solve the operational problem, not just build software.
We define the smallest useful release and decide where AI, automation or conventional software adds value.
We ship in small releases so teams can learn, adapt and reduce risk before it compounds.
We measure adoption, refine the workflow and leave behind a system your team can own and extend.
Measured uptime across selected SBL-managed AI and software workloads, where reliability is part of the engagement rather than an afterthought.
"SBL has put their most experienced staff to work on this assignment. They have always delivered with high accuracy and to the required quality."Leopold J. RomeijnPresident & CEO · Satellite Imaging Corporation
Ask how they will handle data access, model limits, workflow change, security, measurement and maintenance.
Read · 8 min →The hard work is deciding what an agent may do, when it must ask and how every action gets audited.
Read · 12 min →Planning, QA, documentation and support all change when teams use AI inside the engineering workflow.
Read · 10 min →Teams make progress when data ownership, process rules and accountability are clear enough to automate.
Read · 24 min →Focus on access, logging, review paths, failure modes and the person responsible when output is wrong.
Read · 9 min →Tell us what's getting in the way: a legacy system, a manual workflow, fragmented data or an AI initiative that needs a path to production.