Production AI
in weeks.
Not quarters.
Six capabilities across the data and AI stack on Databricks. One team. Zero handoffs. Every engagement aligned to a P&L outcome before kickoff.
Capability 01 · Data Engineering
Data engineering for AI workloads.
A data foundation that outlives your AI roadmap. Modern, governed pipelines on Databricks, built for the use cases you have not deployed yet, so the foundation does not need a rebuild every two years.
What you get
- Unity Catalog deployed in week one
- Streaming and batch ingestion ready for AI workloads
- Medallion data model, production-grade
- Lineage and quality instrumented end to end
- Operational and analytical data unified, no CDC sprawl
- One team owns data plus AI. No translation loss.
Capability 02 · Databricks Migration
Databricks migration without the multi-quarter chaos.
Other firms scope this for two years. We ship in weeks. Fixed-scope migrations from your legacy data warehouse, BI, or data engineering platform. Parallel-run validation. No big-bang cutover. Migrated for the AI you want to deploy next, not just the workloads you run today.
What you get
- Data warehouses · Snowflake, Teradata, Oracle, Synapse
- Hadoop & CDP · HDFS, Hive, MapReduce, Cloudera
- Data engineering · ADF, Fabric, Informatica, custom ETL
- BI platforms · Tableau, Power BI, Looker
- Operational DBs · PostgreSQL, Aurora, MySQL into Lakebase
Capability 03 · AI/ML
Production AI/ML, tied to a P&L outcome.
AI that shows up on the P&L. Not in a deck. Every engagement aligned to a business KPI before kickoff. Cost reduced, cycle time cut, or revenue unlocked. If we cannot tie the AI workflow to a P&L line, we say so before contracts are signed.
What you get
- Production AI workflow live in real business process
- Reusable AI Runtime accelerating delivery
- Governed by Unity Catalog. Auditable end to end.
- Monitoring, CI/CD, and cost guardrails from day one
- Business KPI verified post-deployment
- Platform ready for the next use case
Engagements
Customized fixed-price Projects and ongoing team-based delivery.
Book a Strategy SessionCapability 04 · AI Transformation
AI transformation and modernization.
Stop transforming. Start shipping. For organizations 18 to 36 months into transformation that have realized their stack cannot handle generative AI. We modernize the data estate and operationalize AI in a single coordinated program.
What you get
- Assess · Strategy workshop, KPI alignment, roadmap
- Migrate or Build · Rapid prototyping into production
- Design · Target architecture and governance model
- Optimize · Climb Summit handoff to internal teams
Capability 05 · Modern Analytics/BI
Next-generation analytics and BI on Databricks.
Stop waiting for dashboards. Ask your data anything. Replace per-seat Tableau and Power BI with AI-powered, always-live analytics on Databricks. Self-service in plain English. Governed by Unity Catalog.
What you get
- $0 per-user BI licensing
- 60% lower analytics platform cost at scale
- 100% live data. Zero extracts to maintain.
- 10x faster time to insight on ad-hoc questions
- One semantic layer shared across every consumer
Engagements
Capability 06 · Agentic OS
Agentic OS for enterprise AI.
Production AI agents grounded in your governed data. Multi-step reasoning, tool calling, and retrieval running on a Lakehouse-native foundation. Anthropic-powered for the workloads where reliability matters most.
What you get
- Agents that read and write your governed data
- Retrieval grounded in your own data
- The right model for each task
- Tool calls into your internal systems
- Multi-step workflows you can inspect at every step
- Access controls and audit logs through Unity Catalog
- An evaluation harness that proves it works before rollout
Engagements
Often deployed inside an industry context. Insurance underwriting, clinical workflows, PE portfolio intelligence.
Book an Agentic Strategy SessionPredictable engagements. No surprises mid-quarter.
Aligned to a P&L outcome before kickoff. Owned by one senior team. Handed off cleanly to yours at the end.
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Phase 01 Assess
Outcome alignment
Strategy session with executive stakeholders. KPI defined and signed off before code is written.
Ships: Readiness Report
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Phase 02 Design
Architecture & governance
Target architecture mapped. Unity Catalog model. Migration sequence prioritized.
Ships: Architecture spec
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Phase 03 Build
Migrate or build to production
Domain-by-domain execution. Parallel-run validation. Reusable AI Runtime accelerating delivery.
Ships: Production system
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Phase 04 Optimize
Climb Summit handoff
Runbook transferred. KPI measured against baseline. Internal team self-sufficient.
Ships: Internal team self-sufficient
Why Climb
Built for outcomes, not hours.
If you have worked with a traditional firm or global system integrator, you know the pattern: broad teams, long timelines, time-and-materials expansion, and too much value trapped in decks. Climb is different.
Senior, forward-deployed Databricks and AI teams Fixed-scope engagements tied to measurable outcomes Reusable accelerators, patterns, and delivery runtime Production systems in weeks, then scale One team owns the outcome end to end Typical Consulting Model
Large blended teams with variable seniority Open-ended time and materials billing Rebuilt workstreams and handoffs every engagement Strategy, design, and implementation spread across quarters Client coordinates across practices, vendors, and handoffs What clients ask before engaging.
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001 How is outcome-based pricing structured in practice?
We align on a measurable business outcome before kickoff, then scope the engagement around the production system required to reach it. No open-ended time-and-materials meter.
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002 Do we need to be on Databricks already?
No. Some engagements start on Databricks, and others begin with migration or modernization. The path is scoped around where your data estate is today.
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003 What if our data foundation is not ready?
Then the foundation becomes part of the roadmap. We identify the missing governance, lineage, quality, and pipeline work required before production AI can hold up.
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004 What does the team composition look like on a typical engagement?
A senior team owns the outcome end to end, combining strategy, architecture, data engineering, AI/ML engineering, governance, and delivery leadership without handoffs.
Ready to map your engagement?
Walk away with a Basecamp recommendation and a 90-day roadmap to production. Thirty minutes.