Frequently Asked Questions

We work on project-based engagements, not hourly rates or retainers. Pricing depends on scope, complexity, and timeline. A Discovery Sprint typically costs $15K-$25K and takes 2 weeks. Build Programs range from $75K-$500K+ depending on scale and duration. We provide a fixed proposal with clear deliverables after discovery.

We've found this approach aligns our incentives with yours—we're motivated to deliver value efficiently, and you get predictability around budget and timeline.

Discovery Sprint: 2 weeks. Gives you clarity on what's possible.

Build Program: 4-24 weeks depending on scope. A modern data pipeline might take 8-12 weeks. A full data platform redesign might take 16-20 weeks.

Timeline depends on your availability, data complexity, number of integrations, and how quickly decisions can be made. We provide a detailed timeline during discovery.

Data security and access control are non-negotiable for us. Our standard approach:

• • We work within your data environment (VPC, managed data warehouse, cloud account)
• • We use temporary, project-scoped credentials with minimal required permissions
• • All access is logged and auditable
• • We never extract or store your data outside your systems

Your IT and security teams can review our access patterns and revoke access at any time.

We take security seriously and understand that healthcare, finance, and other regulated industries have specific requirements.

• • We design systems with data residency, encryption, and access controls your compliance team approves
• • For healthcare, we implement HIPAA-compliant documentation and audit logging
• • For PII handling, we follow data minimization and retention policies you define
• • Your security team participates in architecture review and approval before implementation

We're not security experts—your team is. We design systems that comply with what your compliance and security teams require.

We are skeptical of AI too. Hallucinations are real, and we don't believe general-purpose AI is appropriate for mission-critical decisions. Our approach:

• • We use AI for task-specific automation with guardrails: summarization, routine routing, pattern detection
• • For knowledge retrieval, we ground every response in actual documents (RAG, not free-form generation)
• • We implement confidence scoring and fallback procedures when confidence is low
• • We require human review for any decision that impacts operational or compliance risk

AI is a tool to automate routine work and free your team for judgment calls. It's not a replacement for oversight.

We believe in clarity before tooling. Our selection process:

1. 1. Understand your problem and current state (discovery)
2. 2. Define architectural requirements and constraints
3. 3. Evaluate tools against those requirements
4. 4. Recommend the simplest tool that solves your problem

We work with modern, mature, widely-supported tools (Snowflake, BigQuery, dbt, Fivetran, etc.), not niche or bleeding-edge frameworks. Your internal team needs to sustain these systems, so we prioritize tools your team can learn and maintain independently.

Integration is a core part of what we do. Our approach:

• • We prioritize native APIs and SaaS connectors (Fivetran, Stitch, Zapier) over custom code
• • We design error handling, retry logic, and monitoring so integrations fail visibly
• • We handle authentication, rate limiting, and data transformation transparently
• • Every integration is documented and owned by your team after we leave

We'll discuss your system landscape during discovery and provide a clear integration roadmap.

Yes, 100%. Every system is designed for your team to own and evolve. This shapes how we build:

• • We use industry-standard tools and patterns, not proprietary code
• • We write readable, well-commented code your team can understand and modify
• • We provide comprehensive documentation and run knowledge-transfer sessions
• • We stay for 30 days post-launch to help your team stabilize production

At project end, you should feel like these systems are yours—because they are.

Documentation is not an afterthought—it's a first-class deliverable:

• • Architecture overview and system design decisions
• • Data model and schema documentation
• • Deployment and operational runbooks
• • Monitoring, alerting, and troubleshooting guides
• • Well-commented source code and configuration files

All documentation is maintained in Git alongside your code, versioned and reviewed like any other deliverable.

Post-launch maintenance is your team's responsibility. We equip you to do it:

• • We leave comprehensive monitoring and alerting so your team sees problems early
• • We document common issues and troubleshooting procedures
• • We provide 30-day post-launch support to help you stabilize production
• • After that, you can engage us for enhancements or additional services

We design systems to be maintainable by your team, but we're available if you want to extend them later.

Yes. Knowledge transfer is built into every engagement:

• • Hands-on training during development (pair programming, code reviews)
• • Comprehensive documentation your team can reference
• • Formal training sessions at project end
• • 30-day post-launch support with daily standups during the first week

Our goal is for your team to feel confident owning the systems we build.

We work best with:

• • Mid-market to enterprise organizations (typically $50M+ revenue)
• • Teams that want reliable, sustainable systems, not quick hacks
• • Organizations willing to invest in clarity and documentation
• • Teams that plan to own and evolve systems internally
• • Industries where reliability, compliance, and governance matter (healthcare, finance, logistics)

If you're looking for someone to manage your data platform indefinitely as a vendor, we're not the right fit. If you're looking to build internal capability and own your systems, we are.