From kick-off to steady-state operations
A clear path to live: configured from your SOPs, validated as we go, connected to your systems, and measured against your own baseline.
One true automation, from start to end
Most safety teams already have some automation. But it is partial: a tool that reads forms here, a bot that codes terms there. vGenix Ai automates the whole case lifecycle as one flow.
Islands of automation
- Point tools automate one step at a time
- People re-key data and hand cases between systems
- Every case still needs manual touches
- Savings never add up across the lifecycle
One continuous flow
- Every step automated, in one continuous flow
- One platform and data model: no re-keying, no hand-offs
- Zero-touch processing for eligible cases
- Experts routed only the cases that need judgement
Zero-touch lane
Eligible cases flow from intake to E2B (R3) submission and acknowledgement with no manual touch. Eligibility rules, for example non-serious, complete and not a duplicate, are agreed with you and validated before go-live.
Expert lane
Cases that need judgement, such as serious or unexpected events, are routed automatically to the right reviewer, with extraction, coding and checks already done.
Automation, compared
What separates meaningful automation from automation in name only.
| Area | Typical point-tool automation | vGenix Ai |
|---|---|---|
| Scope | One step at a time: intake, or coding, or submission | The whole lifecycle, from intake to acknowledgement and archive |
| Data | Re-keyed between tools and systems | One data model shared by every module |
| Hand-offs | People move cases between tools | None: cases flow automatically |
| Manual touches | Every case still needs some | Zero-touch for eligible cases; experts for the rest |
| Rules | Generic logic you adapt to | Configured from your SOPs, validated and versioned |
| AI | Generative output reviewed by people | Neurosymbolic: every answer checked against rules and knowledge |
| Traceability | Gaps between tools | Every output linked to its source, in one audit trail |
| Validation | After the build, as a separate project | As we configure, with evidence from the implementation itself |
| Proof | Headline percentages | Results measured against your own baseline |
Four phases to live
Durations depend on scope and are agreed with you during scoping.
Scope & design
- Modules, domains and markets agreed
- Current workflows and SOPs mapped
- Data sources and integrations confirmed
- Baseline metrics agreed and measured
Deliverables: Project plan · scope document · baseline report
Configure & validate
- Case rules, coding conventions and thresholds configured
- Templates, narratives and review gates set up
- Zero-touch eligibility rules agreed
- Validation run as each part is configured
Deliverables: Configuration specification · validation evidence
Integrate & onboard
- Safety database and gateways connected
- Access, roles and SSO set up
- Data migration where needed
- Users trained by role
Deliverables: Integration tests · training records
Go live & operate
- Controlled release, module by module
- Dashboards from day one
- Hypercare period after go-live
- 24/7 support and continuous improvement
Deliverables: Go-live report · results against baseline
A 6-week pilot on literature monitoring
Prove the value on your own data before you commit to the full platform.
Scope and baseline
Agree the literature scope, sources and success measures; measure the current baseline.
Configure
Search strategies, screening rules and review gates set up from your SOPs.
Validate
Configuration tested and validation evidence produced with your QA team.
Run on live data
vGenix Ai runs alongside your current process on real articles.
Measure and decide
Results reported against the baseline, with a recommendation for next steps.
Example plan. The pilot scope and timeline are agreed with you.
Who does what
| Area | Your team | vGenix Ai |
|---|---|---|
| Project leadership | Project sponsor and safety lead | Implementation lead and project manager |
| SOPs and rules | Provide SOPs; approve configuration | Map SOPs; configure rules, templates and gates |
| Validation | QA review and approval | Validation approach, test execution and evidence |
| Integration | IT access and system owners | Connectors, gateways and data migration |
| Training | Nominate users and super-users | Role-based training and materials |
| After go-live | Own operations and decisions | Hypercare, 24/7 support and improvements |
Support that keeps improving
Hypercare
Close support in the weeks after go-live while your team settles in.
24/7 support
Multi-tier support and a named customer success team.
Results reporting
Regular reports on cycle time, quality and timeliness against your baseline.
Controlled improvement
New rules, modules and AI improvements released under change control.
Intelligent safety should be one connected operation
Automate the work. Keep the decisions with your experts. Keep the evidence traceable. See it on your own data in six weeks.
6-week pilot on literature monitoring
- Baselines agreed up front
- Configured to your SOPs
- Measured on your own data
- Validation evidence from day one