Problem framing
Translate broad AI ambition into a specific decision, workflow, user, owner, and desired end state.
AI Readiness Scan
Before the AI pilot, find the decision.
The AI Readiness Scan is a 1-2 week diagnostic for life sciences teams that need to decide what to fund, fix, or stop before AI momentum becomes expensive.
SignalForge inspects the decision target, evidence chain, data condition, workflow reality, ownership model, vendor assumptions, and review burden. The output is a practical recommendation: what is ready, what is fragile, what needs repair, and which bounded pilot, if any, deserves funding.
What you buy
A short, written, decision-focused diagnostic.
A SignalForge Scan is not a strategy deck, implementation sprint, model build, vendor resale, or open-ended advisory conversation. It is a structured outside review of the decision, evidence chain, data condition, workflow reality, ownership model, review burden, and smallest defensible next move.
Typical output
- Primary problem statement
- Evidence-chain map
- Readiness and risk register
- Pilot / repair / buy / defer / stop recommendation
- Executive memo written for action
Low-friction first step
A sanitized problem summary is enough.
The first conversation does not require broad data access, confidential files, or a polished internal brief. Workflow notes, public materials, schema excerpts, screenshots, vendor summaries, anonymized examples, or a plain-language description of what is stuck are enough to determine whether SignalForge can help.
Four questions before spend accelerates.
Evidence inspection
Inspect the data, documents, assays, omics outputs, computational artifacts, vendor inputs, and assumptions that would have to support the workflow.
Readiness triage
Separate use cases ready for a pilot from those needing metadata, repository, governance, review, or process repair first.
Pilot or stop recommendation
Define the smallest defensible next move: pilot, repair, buy, defer, keep manual, or stop.
What leadership receives
Decision artifacts, not a generic strategy deck.
Primary problem statement
A plain language description of the decision or workflow the AI effort is supposed to improve.
Evidence chain map
A map of the records, handoffs, systems, people, and assumptions that support the decision today.
Readiness and risk register
A concise view of data gaps, metadata gaps, workflow gaps, ownership gaps, vendor risks, and review burdens.
Pilot recommendation
A bounded first project with success criteria, stop criteria, required inputs, review gates, owner accountability, and expected decision value.
Executive memo
A direct recommendation on what to fund, fix, test, pause, reject, or monitor.
Best fit triggers
Use the Scan before the organization locks into a path.
- Leadership wants an AI roadmap, but the first use case is unclear.
- A vendor claim looks strong, but real workflow fit is unknown.
- A private RAG, agent, model, or analytics idea depends on messy evidence.
- A pilot is being proposed without stop criteria, review burden, or decision owner.
- The team needs to know whether to fund, fix, or stop.
What happens next
Start the client fit screen
Send the use case, evidence sources, and decision your team is trying to improve. SignalForge will help determine whether it is ready for a Scan, needs narrower framing, or should not become an AI project yet.