Three ways
to work together.
Every project gets scoped to the actual situation. These tiers are a starting point, not a fixed menu. Complex projects receive custom proposals.
A two-week fixed-scope engagement to validate your AI idea before committing to a full build. Honest answers before serious money.
- Technical feasibility assessment
- Data readiness audit
- Working prototype or proof of concept
- Architecture recommendation report
- Clear go or no-go recommendation
- One revision cycle included
Defined scope, milestone-based delivery. From raw data to deployed model with documentation, monitoring, and a 60-day support window.
- Everything in Discovery Sprint
- Full model development and training
- Production deployment and infrastructure
- MLOps setup with drift detection
- Complete technical documentation
- 60-day post-launch support
- Full IP ownership transferred to client
A senior ML engineer and data scientist embedded in your team on a monthly retainer. Ongoing development, continuous improvement, and direct access.
- Dedicated two-person ML team
- Weekly syncs and async collaboration
- Continuous model iteration
- Model monitoring and incident response
- Quarterly strategy reviews
- Priority response SLA
- Minimum three-month engagement
Custom Program
Large-scale transformation programs, multi-team augmentation, white-label builds, and long-term AI partnerships. Every term is negotiated around your specific situation.
Before you reach out.
Both. The Discovery Sprint tier was specifically designed for early-stage companies that need technical validation before fundraising or committing to a full build. We have worked with pre-seed startups and listed enterprises. The engagement model scales to the situation.
Discovery Sprints take two weeks. Project Builds typically run six to fourteen weeks depending on data readiness and model complexity. Most delays we see in production AI projects are caused by data issues discovered mid-project, which is exactly why the Discovery Sprint exists — to surface those problems cheaply.
You do. All code, models, weights, and documentation produced under a Project Build or Dedicated Team engagement are transferred to the client in full. We sign IP assignment agreements before any work begins.
Yes, and this is actually the recommended path for most clients. Start with a Discovery Sprint to validate feasibility and data readiness. If the findings are positive, move into a Project Build. Many of our longest-running clients began with a two-week discovery that cost under $8k.
Project Builds include a 60-day post-launch support window covering bug fixes, performance monitoring, and model drift alerts. After that, clients can continue on the Dedicated Team retainer for ongoing improvement, or move to a lighter maintenance agreement. We do not disappear after deployment.
Healthcare (clinical NLP, medical imaging, HIPAA-compliant AI), financial services (fraud detection, credit risk, investment research), real estate (automated valuation, document processing), e-commerce (recommendation engines, demand forecasting), and education technology. See our case studies for detailed examples from each vertical.
Not sure which tier fits?
Book a call and we will recommend the right starting point for your situation.
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