years running frontline operations
Independent · operator-led · New York / remote
Digital Intelligence implementation & systems advisory
Digital Intelligence that earns its place in the business.
Keith helps small and mid-sized businesses find the right Digital Intelligence opportunity, build the system responsibly, and put it into operation—with 22+ years running real-world operations and a production multi-model runtime behind the work.
Operational judgmentProduction DIOne accountable builder
01 Operating evidence
The work has to survive contact with the real world.
months designing & shipping a multi-model Digital Intelligence runtime
operating principle: business process before tool recommendations
engagement tiers — every one ending in documentation & a real handoff
02 Ways to start
Start with the shape of the problem.
Every engagement is bounded before it begins. Pick the level of clarity or capacity you need, then we make the next decision visible.
Digital Intelligence Opportunity Audit
For leaders who know Digital Intelligence matters but do not know where to start.
1–2 weeks · From $2,500
A ranked view of where Digital Intelligence can earn its keep—before you commit to a build.
- Workflow and constraint map
- Build-versus-buy guidance
- 90-day action plan
Bespoke Digital Intelligence Agent / System Build
For teams ready to turn one ranked opportunity into a production system.
Typically 3–8+ weeks · From $5,000
A bounded, working system with the controls and documentation to operate it.
- Written scope and acceptance criteria
- Evaluation and reliability controls
- Documentation and handoff
Fractional Digital Intelligence Advisory / Agent Trainer
For teams that need ongoing judgment, governance, and capability-building.
Monthly · From $2,500 / month
A practical thought partner who keeps the roadmap, team, and system honest.
- Roadmap and cost review
- Team training and evaluation discipline
- Incident diagnosis and governance
Secure Command Center Laptop quoted by scope
Training & Handoff from $1,500 · typical $2,000–$4,000
03 Proof of work
See what the work actually produces.
These sample deliverables show the consulting model in concrete form: diagnose the opportunity, constrain the system, define the evidence, then make the implementation decision explicit.
Find the bottleneck before you build around it.
A practical assessment of where AI can reduce friction, where it should not be trusted yet, and what evidence is needed before investment.
Build the smallest system that can earn its keep.
A six-week human-in-the-loop implementation plan with scope boundaries, governed retrieval, acceptance gates, operating ownership, and handoff.
SAMPLE ARTIFACTS Illustrative consulting deliverables, not client results. The point is to make the method inspectable.
04 The engagement
Clarity before complexity.
Good implementation is not a magic trick. It is a sequence of decisions you can see, challenge, and own.
- 01
Discovery call
We confirm the business problem, urgency, owner, data, constraints, and whether there is a real fit.
- 02
Fixed-scope proposal
Outcome, deliverables, exclusions, timeline, price, responsibilities, and acceptance criteria—written down.
- 03
Build or advise
Work moves through visible milestones. Uncertainty is surfaced early, not buried in the handoff.
- 04
Handoff
You receive documentation, operating guidance, known limitations, and a walkthrough for the next owner.
05 A useful boundary
SMALLEST USEFUL SYSTEMTechnology follows the constraint.
I look for the current-state cost, quality risk, and adoption burden first. Then I recommend a system sized to the opportunity—not a stack looking for a reason to exist.
Start with the business process, not the tool.
The smallest system that can earn its keep is usually more valuable than the most impressive system you could build.
No open-ended dependency. No unlimited on-call promise. No implied transfer of your operating function.
06 Repository-backed proof
A production Digital Intelligence runtime, described without the theater.
Behind the advisory work is an operating system for multi-model collaboration: retrieval, evaluation, voice and profile work, diagnostics, and governed data handling. The point is not to claim that every possibility is solved. It is to know where the edges are.
Ask about the architecture- 01Multi-model orchestration
- 02Retrieval-aware context
- 03Evaluation and diagnostics
- 04Voice and profile work
- 05Governed data handling
Built to be inspected, not mythologized.
07 Trust, ownership, continuity
Useful systems should leave you more capable.
Security and handoff are not an afterthought. They are part of the definition of done.
Client-controlled access wherever practical, with approved credentials and least-privilege boundaries.
Data minimization as a working practice, not a line in a policy document.
Documented ownership boundaries so the next operator can understand what they inherited.
Secure handoff rather than a permanent dependency on the person who built it.
08 Field note /
NECESSITY, NEVER INTENTIONA note on how I see systems
The audience sees light. The operator sees the chain of small decisions that makes the light possible.
Years in projection booths and frontline operations taught me to pay attention to consequences: the invisible choice, the failure mode, the handoff path. That is the same lens I bring to Digital Intelligence. Systems are experienced through what they make possible—and what they make difficult.
Earlier career: one of few nationally proficient IMAX projectionists — trained on the system by IMAX's own technicians, then ran three-day crash courses for visiting cinema teams.
Read the lived credentials09 Start a conversation
Make the next decision visible.
Tell me what you want to build, fix, or understand.
Bring the messy version. We can decide whether there is a real opportunity, what the smallest useful next step is, and whether I am the right person to help.