Services built for operating companies.
We offer four integrated services. Most projects use all four. Some start with one and expand based on what the data reveals.
Data Foundation Engineering
Source audits, warehouse architecture, ingestion pipelines, data modeling, transformation logic, data quality checks, lineage documentation, and team enablement.
What we deliver
- ✓ Complete source system audit and data lineage
- ✓ Warehouse or data lake architecture (Snowflake, BigQuery, etc.)
- ✓ ELT pipelines with monitored data quality
- ✓ Data models and transformation logic
- ✓ Documentation and runbooks
Ideal for
Organizations with fragmented data, inconsistent reporting, and the need for a single reliable foundation.
How we approach it
Week 1–2: Discovery Sprint
Interview stakeholders. Audit all data sources. Define scope and success metrics. Agree on architecture.
Week 3–8: Build Phase
Implement warehouse. Build pipelines. Create data models. Add quality checks. Set up monitoring.
Week 9–10: Operational Handoff
Train your team. Document everything. Establish ownership model. Support first week of live operations.
How we approach it
Week 1: Metric Definition
Work with ops teams to define every metric. Agree on calculations, refresh schedules, and who is accountable.
Week 2–4: Build & Test
Create dashboards and operational reports. Test against source data. Reconcile with legacy reports.
Week 5–6: Adoption & Training
Train your teams. Run parallel reporting. Address concerns. Go live when confidence is high.
Reporting That Operations Trusts
Metric definitions, executive dashboards, operational reporting, refresh reliability, exception views, and adoption training.
What we deliver
- ✓ Documented metric definitions (calculation, frequency, owner)
- ✓ Executive dashboards with drill-down capability
- ✓ Operational reporting (daily/weekly/monthly)
- ✓ Automated exception alerts
- ✓ Team training and documentation
Ideal for
Teams that don't trust their current reports. Organizations using multiple disconnected reporting tools. Anyone rebuilding reporting after mergers or system changes.
Practical AI Workflow Automation
Document classification, intake triage, knowledge retrieval, summarization with review gates, workflow routing, and monitored human-in-the-loop automations.
What we deliver
- ✓ Intake triage and routing automation
- ✓ Document classification (human-reviewed)
- ✓ Summarization with quality gates
- ✓ Knowledge retrieval (context for human review)
- ✓ Workflow routing and orchestration
- ✓ Quality monitoring and feedback loops
Ideal for
High-volume intake processes. Document-heavy workflows. Any repetitive back-office task that follows logic but requires context.
Our automation philosophy
AI works best when the rules are clear and exceptions are expensive. We automate the main path and route edge cases to your team with full visibility.
Clear inputs
Document or form submission, structured data, explicit rules.
Measurable output
Dashboard metrics on accuracy, processing time, and exception rate.
Accountable ownership
Your team owns the process, understands the logic, and runs it.
Human review where it matters
We don't remove humans—we route them to the decisions that require judgment.
How we approach it
Month 1: Audit & Establish Ownership
Review current monitoring. Identify data quality issues. Define ownership model.
Month 2–3: Implement Monitoring
Set up alerts. Build runbooks. Create escalation paths. Train on-call rotations.
Ongoing: Optimization & Support
Monthly reviews. Incident analysis. Process improvements. Scale as your data grows.
Data Reliability & Enablement
Monitoring, alerts, ownership models, runbooks, team training, and ongoing optimization.
What we deliver
- ✓ Data quality monitoring and alerts
- ✓ Incident response runbooks
- ✓ Ownership and escalation models
- ✓ Team training (operations and analytics)
- ✓ Quarterly optimization reviews
Ideal for
Any organization with production data systems. We typically start this in parallel with building the foundation or reporting, and continue long-term.
How we work with you.
Discovery Sprint
1–2 weeks. We audit your current state, interview stakeholders, understand your constraints, and propose scope and timeline.
Outcome: Agreed roadmap and project structure.
Build Phase
4–12 weeks depending on scope. We build systems, run parallel testing, address feedback, and prepare for transition.
Outcome: Live systems, documentation, initial training.
Operational Handoff
2–4 weeks. Your team takes ownership. We train, document, establish escalation paths, and support the first month.
Outcome: Independent, owned systems. You're not locked in.
What we don't do
- — Black-box automation. We document every workflow.
- — Long-term outsourcing. We train your team and hand it over.
- — Generic templates. We build for your specific operations.
Ready to start?
Let's discuss which service is the right starting point for your team.
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