01
Senior judgment is missing
Your engineers can build, but need a partner for architecture trade-offs, data reviews, go-no-go decisions and priorities across business and technology.
WHY AI / FRACTIONAL DATA & AI
Senior Data & AI capacity, inside your team.
Your team needs experienced judgment and hands-on delivery, but not a full-time hire. Work with a principal consultant for an agreed number of days each month, from data foundations to production AI. Bring a use case, or start by finding the right one.
Discuss fractional supportWHO THIS HELPS
A team to work with. A gap to close.
02
Delivery needs a working partner
You need someone who joins the team rhythm, helps implement pipelines or AI workflows, reviews the result and leaves decisions your team can use.
03
The next move is unclear
You have data and business pressure to use AI, but no well-scoped use case. The first block can establish priorities and constraints before any build begins.
RESPONSIBILITY AND OUTPUTS
Decisions and delivery that stay with your team.
01
Architecture and priorities
A prioritized plan, architecture reviews and decision records explaining options, assumptions and trade-offs. Agree which decisions the consultant owns and which require your approval.
02
Hands-on implementation
For Embedded and Intensive: agreed pipeline, ML, LLM, agent or infrastructure work. Example outputs include a reviewed pipeline, an evaluation harness or a release checklist for a selected initiative.
03
Team capability
Working sessions, code or design reviews, and operating documentation. The aim is to make the work understandable to the people who will continue it.
These are examples of outputs to scope, not a promise to deliver every item each month. Capacity is reserved time; completed outcomes depend on priorities, access and dependencies.
EXISTING PACKAGES
Choose the monthly capacity, then agree the work.
01
Advisory
4 days per month. Minimum 3 months. Team exists; need senior Data & AI judgment. Architecture and data reviews, go-no-go, priority plan, async in an agreed window.
02
Embedded - default
8 days per month. Minimum 3 months. Want hands-on in the team rhythm. All Advisory plus a weekly embedded day: pipelines, ML/LLM/agents, and production care on 1-2 initiatives. If there is no use case yet, the first days are clarity, then we build.
03
Intensive
> 8 days per month. Minimum 3 months. Deep push / multiple workstreams. All Embedded plus heavier hands-on across data, AI, and infra.
Advisory is senior review and direction. Embedded adds a weekly embedded day within the 8-day monthly pool on 1-2 initiatives. Intensive increases capacity for a deeper push or multiple workstreams. We agree scheduling and the async response window before starting.
WORKING RHYTHM
A shared backlog, visible decisions, regular review.
01
First block: establish the baseline
Meet the business and technical owners, review the current architecture and backlog, and agree the first priorities. If no use case exists, establish a practical one before implementation.
02
During the month: work with the team
Reserve agreed days, join relevant planning or design sessions and deliver against the selected work. Keep decisions, open risks and dependencies visible in the team's existing tools.
03
Monthly review: decide what comes next
Review completed work and capacity used, inspect blockers and agree the next block. Adjust priorities explicitly instead of treating the retainer as unlimited availability.
An example Embedded month: review architecture and pick one pipeline gap; implement and test the selected flow with the team; add evaluation or operating checks; hand over the changes and review the next priority. The exact allocation follows the agreed backlog.
EVIDENCE AND LIMITS
Principal capacity, with a clear boundary.
Read Aleksander's background to see who works with your team, and the P.R.O.D. framework to inspect how readiness is assessed. The data foundations service explains the assessment, architecture and pipeline work that can also fit an agreed monthly backlog.
In the monthly pool: ETL / lakehouse / DWH, orchestration, ML / LLM / agents, production (evals, access, cost), and business intelligence or apps when they serve the system. Use-case clarity when it is missing.
Out of the monthly pool: large greenfield products, 24/7 ops, and formal security / pen tests - those are a separate scope (Audit, Sprint, Ownership, or custom).
This is a principal consultant engagement. Your team retains business approvals, access administration and operational roles unless responsibility is explicitly agreed. Capacity is not a multi-specialist subscription or a guaranteed full-time replacement.
BUYER QUESTIONS
Choose the right engagement boundary.
Can we start without an AI use case?
Yes. Use-case clarity can be the first block. We examine business workflows and data constraints, then decide whether there is a useful build to pursue.
When is a project a better fit?
Choose a project when you need a defined deliverable and a bounded timeline. Choose fractional when recurring judgment and delivery capacity across changing priorities are more useful.
Does the monthly pool include production care?
Agreed evaluations, access, cost and safe iteration can fit the pool. Continuous 24/7 operations and formal security testing do not. Ownership of a specific production system is a separately scoped engagement.
What should we bring to the fit call?
Current team roles, the main delivery bottleneck, available technical access and the amount of senior support you expect to need. We agree responsibilities and scheduling before the engagement begins.
NEXT STEP
Start with the problem you need to solve.
Bring your current priorities, team structure and the decisions or delivery work that need senior support. The fractional fit call helps choose a capacity package and a useful first month. No working AI demo is required.