Product
Six evidence modules. One Attribution Stack.
TimeToPoint ships as six modules built on the same Attribution Stack record schema. Start with one workflow. Add modules as your evidence questions deepen.
One record schema. Six deployment shapes.
TimeToPoint produces one type of artefact — a structured Attribution Stack record — packaged for the buyer who needs it. The same evidence schema that produces a Work Attribution Record for HRD also produces a Counterparty Evidence Report for an auditor, a Verified Bill record for a CFO, or an Agent Boundary record for a CTO.
Starting with one module does not lock you out of the others. The records compose.
SKU 1 — Work Attribution Record
For: HR leaders, People Operations, team leads, project owners, delivery managers, and AI-using contributors
AI-assisted work makes it harder to know who actually contributed what. Performance reviews, bonus calculations, and vendor invoices all assume contribution is visible. AI weakens that assumption.
Creates a record showing human contribution, AI contribution, review points, accepted outputs, and evidence of completion — across all six Attribution Stack layers.
Human + AI contribution map
Layer 2 — who contributed which part.
Review and acceptance trail
Layer 4 — who reviewed, accepted, or escalated.
Outcome record
Layer 5 — what happened after the work was used.
Boundary note: TimeToPoint surfaces contribution evidence. Compensation, performance, and credit decisions remain with HR, finance, and the project owner.
See a work attribution sampleSKU 2 — Agent Boundary Register
For: CTOs, product leaders, AI platform teams, risk teams
Teams deploy AI agents faster than they define task boundaries, authority, and escalation points. Controlled use works. Approved operation stalls because risk and compliance teams cannot prove the agent stayed in scope.
Maps which agent can act, what it can access, what tools it can use, when it must escalate, and what evidence each action should leave. Generates per-tool-call evidence records (Layers 3 and 4).
Agent authority map
Tool-use boundary record with escalation and exception markers.
Per-action evidence
Evidence record for each tool call in the workflow.
Production-readiness pack
Evidence supporting the move from controlled use to approved operation.
SKU 3 — Verified BillOps by TimeToPoint
For: CFOs, finance controllers, procurement, vendor managers
AI agents, SaaS platforms, and automation create costs before finance fully understands what happened. The CFO question is no longer "what did we spend?" — it is "was this cost real, necessary, authorised, attributable, and payable?"
CFO AI Bill Evidence Brief
From £1,500 + VAT · 10 working days
One month of billing data. Payment evidence report covering one workflow.
SKU 4 — AI Exposure Evidence Layer
For: CTOs, risk teams, security teams, operations leaders
AI lowers the cost of producing activity, claims, and outputs. That includes synthetic submissions, unsupported completion claims, agent overreach, and uncontrolled tool use.
Creates a reviewable record around suspicious workflow patterns, low-evidence activity, and boundary exceptions — so the human reviewer can act faster on signals that already exist.
What it does not do: detect fraud autonomously, make security decisions, or replace SIEM, EDR, or identity tooling.
Assess my AI exposureSKU 5 — Counterparty Evidence Report
For: Clients, insurers, auditors, reviewers, assurance teams, regulated counterparties
Internal records often make sense only to the team that created them. Counterparties — clients, insurers, auditors, regulators — need a record they can inspect without reconstructing the whole workflow.
Packages actor, authority, action, review, and outcome (Attribution Stack Layers 1–5) into a reviewer-facing report. Exportable, retention-ready, cryptographically signed and tamper-evident in higher-assurance deployments.
Boundary note: TimeToPoint produces evidence; reviewer decisions remain with the auditor, certifier, underwriter, regulator, or client.
See a counterparty reportSKU 6 — Evidence Workflow Adapter
For: Operations, engineering, IT, workflow owners
Evidence lives across disconnected tools — workflow systems, finance platforms, identity tools, observability logs, AI platforms, document stores. None of them produces evidence-grade output.
Connects selected signals from existing systems into a TimeToPoint evidence model. Native OpenTelemetry GenAI ingestion is included today. MCP sidecar attestation and Sigstore-signed receipts are scoped for higher-assurance deployments.
Check my integration fitHow a TimeToPoint engagement starts.
1
Choose the workflow
2
Define actor and authority
3
Set evidence boundaries
4
Connect signals
5
Mark review points
6
Generate evidence records
7
Export for reviewer
8
Refine the workflow baseline
Privacy-conscious by design.
Better evidence does not require invasive monitoring. TimeToPoint is designed around workflow-scoped evidence, not keystrokes, screen recording, personal surveillance, or generic productivity scoring.
The goal is to show whether an action should count — not to watch everything a person does.