Axis 1
Right actor
The named contributor, vendor, or AI agent is the one actually doing the work — not a substitute or delegated downstream actor.
Time-to-Point demo
What work verification looks like
Time-to-Point verifies whether work was completed by the right actor, within the right scope, and with enough evidence to be accepted, counted, or paid.
Designed for offshore teams, vendors, and AI-assisted workflows.
Why teams use this
Before paying, accepting, or counting — verify
As teams rely more on offshore engineering, external vendors, and AI-assisted execution, the line between "work was done" and "the right work was done by the right actor" is easy to lose. Time-to-Point makes that line visible and defensible.
What it verifies
Four verification axes
Axis 2
Right scope
The work performed falls within the agreed, authorised scope — not adjacent, out-of-scope, or scope-creeping activity.
Axis 3
Right evidence
The trail of activity is strong enough to support acceptance, billing, or counting — not just a claim of completion.
Axis 4
Right treatment
The decision to accept, review, partially accept, or reject follows policy — not improvisation under pressure.
Example work verification summary
What one verification looks like
A fictional but representative sample for a single work submission from an offshore engineering vendor.
Status
Conditionally valid
Work completed, but evidence gaps present. Accept with review or hold final payment.
Scope match
87%
Most submitted work falls within authorised scope; some tasks appear adjacent or unverified.
Evidence strength
Moderate
Activity trail exists but shows session inconsistencies and partial coverage across claimed work.
- Claimed hours: 142
- Evidence-supported hours: 98
- Review zone: 28
- Scope-adjacent or unverified: 16
⚠ Conditionally Valid — Accept With Review
Work submission credibility
Confidence: 65%
Signals
- Partial scope match between claimed and authorised work
- Execution gaps during claimed active hours
- Session inconsistency across devices and timelines
Recommended action
Accept with review or hold final payment pending clarification on scope-adjacent items.
Why work gets flagged
Four common patterns that reduce credibility
Scope drift
Work that quietly moves outside the authorised scope over time, especially across multi-week engagements.
Actor ambiguity
Unclear whether the named contributor is the actual executor, or whether execution was re-delegated downstream.
Thin evidence trail
Activity logs that show claims but lack corroborating signals across tools, systems, or timelines.
AI-assisted opacity
Work produced with AI assistance where the boundary between human judgement and machine output is not documented.
Use cases
Where work verification matters most
Offshore engineering
Verify that distributed teams are delivering the right scope with evidence strong enough to support acceptance and billing.
Vendors and contractors
Tighten acceptance decisions on external work — especially across long-running or multi-phase engagements.
AI-assisted workflows
Make AI-assisted output auditable: what was human judgement, what was machine output, and where review is required.
How to adopt
Start with an evidence layer, not a rebuild
Time-to-Point sits alongside existing project tracking, time reporting, and delivery systems. It produces an evidence layer that teams can use to tighten acceptance decisions without replacing the stack they already have.
Most teams start on one engagement — typically an offshore vendor or a high-stakes AI-assisted project — and extend from there.
Explore work verification
See how Time-to-Point verifies the right actor, the right scope, and the right evidence.
Evidence-first. No heavy integration required.