The new model offers our clients a dedicated, optimally staffed product team under a single monthly fee. We take on responsibility for delivery, KPI compliance, and regulatory compliance.
Managed Capacity is an engagement model created specifically for clients whose product roadmaps change frequently and for whom standard outsourcing contracts don’t work due to their rigidity and limited adaptability to evolving requirements.
How the Managed Capacity model works
Within the Managed Capacity model, we put together a cross-functional team of 3–8 specialists (software development, AI, data, , QA, DevOps, and design) and work under a single monthly contracted fee.
We take on recruiting, onboarding, mentoring, day-to-day team management, and meeting the agreed KPIs. At the same time, the client retains control over project priorities, the roadmap, and the direction of product development. Delivery, staffing, and compliance risks are on us.
Every engagement rests on three documents that we prepare jointly with the client:
- Master Service Agreement (MSA) captures operational rules, escalation paths, rotation procedures, and the boundaries of the service.
- Statement of Work (SOW) describes team composition, governance structure, and the key objectives the team works toward.
- Service Level Agreement (SLA) sets measurable commitments on quality, delivery, financial, and engineering KPIs.
Product roadmaps are accelerating, and AI initiatives are reshaping priorities mid-sprint. In this environment, fixed-scope contracts often turn out to be too rigid, while per-hour staff augmentation adds management overhead without guaranteeing a measurable outcome. We designed Managed Capacity specifically to close that gap.
— Alexey Spas, CEO of Instinctools.
Ready for regulated industries and AI projects
Regulatory pressure remains one of the top concerns for enterprises in 2026, and we have built Managed Capacity with this in mind. As part of the agreed service level, we take on responsibility for compliance with GDPR, CCPA, HIPAA, PCI DSS, the EU AI Act, and NIST AI RMF.
The model is also well suited to AI initiatives, where, according to industry data, up to 85% of projects never reach production. The Managed Capacity for AI configuration brings together data scientists, AI engineers, MLOps specialists, and domain experts under a dedicated AI Delivery Manager. We build in MLOps practices and governance from day one, rather than bolting them on after the prototype.
Traditional models often respond to change by adding process complexity, and it’s precisely this level of control that usually slows delivery down. Managed Capacity is designed so that adaptation is the norm: we absorb volatility instead of resisting it.
— Alexey Spas, CEO of Instinctools.
The Managed Capacity model is available to Instinctools clients worldwide in dedicated configurations for product development, software modernization, and AI agents implementation.
