Service · Technical Feasibility Study
Find out if it can be built before you pay to build it
We check the idea against the data you actually hold, the systems you actually run, and the team you actually have. You get a yes, a no, or a yes-with-conditions, each with the reason and the cost next to it.
- We inspect your real data and integrations, not a description of them
- Every blocker is written with what it would take to clear it
- Fixed fee and fixed window, usually one to two weeks
- The document is yours whether you hire us for the build or not
What you get
Deliverables, not slideware
- 01
Data readiness read
What exists, where it lives, how complete it is, and what would have to be fixed first.
- 02
Integration map
The systems involved, their access model, and whether they can be read and written safely.
- 03
Risk and blocker list
Each risk with severity, likelihood, and the cheapest way to remove or contain it.
- 04
Verdict memo
Build, build with conditions, or do not build — with a cost and effort range for each path.
- 01question: can quotes be generated from CRM + pricing sheet?
- 02data: 3 years of deals, 8% missing line items
- 03blocker: pricing sheet is manual, no version history
- 04cost to clear blocker: ~1 week of data work
- 05verdict: BUILD WITH CONDITIONS — fix pricing source first
How it runs
What actually happens, step by step
No discovery theatre. Each step ends with something you can read or use.
- 01
Frame the question
One sentence the study has to answer.
- 02
Inspect
Data samples, systems, access rules, current volumes.
- 03
Test the hard part
The riskiest assumption gets checked first.
- 04
Price the paths
Cost and effort for each viable route.
- 05
Write the verdict
A memo an owner can act on without a translator.
Tangible
What lands in your hands
Named objects with a format and a week attached, so the handover is easy to picture.
Verdict memo
Build, build with conditions, or do not build — with the reason attached.
PDF · 9 pagesWeek 2Data readiness read
What exists, how complete it is, and what has to be fixed first.
Findings tableWeek 1Risk and blocker list
Each risk with severity and the cheapest way to remove it.
Ranked listWeek 2
Feasibility Verdict
Can it be built on your data — with the blocker and the cost to clear it.
This is the real template, with client figures replaced by representative ones. Read it before you talk to us — if the format is not useful to you, the engagement will not be either.
Before and after
What the change looks like in the week
Red is the cost you carry today. Green is what the system gives back.
Today
- Nobody can say whether the data supports the idea
- Estimates swing by a factor of five between vendors
- The risky part is left for later, then kills the project
- The decision waits on a meeting that keeps moving
After
- A written answer grounded in your own systems
- A cost range with the assumptions listed underneath
- The riskiest assumption tested first, not last
- A decision you can defend to a board or a bank
Objections
Answered before you ask
How is this different from a PoC?
A feasibility study is analysis and a small targeted test; a PoC is a working pilot on your data. If the study says the only way to know is to build a narrow version, we tell you that and scope the PoC.
What if the answer is no?
Then you saved the build budget. We write down why, and what would have to change for the answer to become yes.
How long does it take?
One to two weeks from access, at a fixed fee agreed before we start.
Keep going
Where people look next
Related work, the category this sits in, and the proof behind it.
One next step, and it is a paid one on purpose
The AI Opportunity Diagnostic is a fixed-scope engagement. You leave with a ranked plan you can act on with us or without us.
Still sizing the problem? Write to us in your own words first. A person reads it.