A compliance automation platform that connects your 6 systems, eliminates manual data entry, and gives your team a single place to see the full picture on any counterparty.
Today, the same data is entered by hand across Sumsub, Elliptic, Asana, Fireblocks, Google Drive, and Google Sheets. Every status change, KYC update, and KYT alert requires a manual update in multiple places. There is no central view.
Workflows that connect your systems. When something changes in one place, the others update automatically. Track A covers the 4 core data synchronisation workflows. Track B adds Fireblocks activation and full Slack bi-directional integration.
Search any counterparty. See current status across all systems in a cards view. Track B adds a full chronological timeline: every action, alert, review, and decision logged in one place. The dashboard reads from your existing systems — it does not become a new database.
Outbound: onboarding completions, status changes, and alerts posted to your topic channels. Inbound: discussions in Slack that require follow-up automatically create Asana tasks or trigger investigations. No context switching required.
Track A is the core platform: 4 workflows, status cards dashboard, no Slack. Track B is the full build: all 6 workflows, timeline dashboard, full Slack, and data export.
Not included in either track: multi-role RBAC, mobile app, integrations outside the 6 listed systems, Slack messages surfaced inside the dashboard (pending your internal privacy review — available as a future add-on).
The design phase is the same for both tracks: 3 focused sessions over 3–4 weeks. The output is a signed-off technical specification and a privacy spec that covers data flows, retention, and GDPR Art. 28 scope. Build starts only after sign-off.
Walk through each of the 6 workflows as they exist today. We document every system, every manual step, every handoff. This is the source of truth for the build specification.
Define the target workflows. Jointly map what data flows through AdapttoAI infrastructure during processing, what is persisted and where, and what GDPR Art. 28 obligations apply. Output: a draft privacy spec your team can validate internally.
Walk through the full technical spec and privacy spec. Align on track choice. Sign off. Build begins.
3–4 hours per session. Total time investment from your team: approximately 10–14 hours.
Monthly subscription starts the month after the system goes live (Month 4 for Track A, Month 6 for Track B). No subscription fee during the build phase.
Wincent operates in a regulated environment. We treat data handling as a first-class design decision, not an afterthought. Here is our current position and what the design phase will confirm.
The platform connects your existing systems. Personal data flows through our infrastructure during workflow execution (routing, transformation, triggering). Our goal is a minimal data footprint: we do not replicate your client database, and nothing is persisted beyond what is operationally necessary for the workflow to function.
Session 2 produces a privacy spec: exactly what data fields pass through our infrastructure, for how long, and under what conditions. Until that mapping is done, we will not make commitments we cannot verify.
Where personal data passes through our infrastructure during processing, AdapttoAI acts as a data processor (Art. 28 GDPR). We sign a Data Processing Agreement as part of the contract. The DPA scope is defined by the design-phase privacy spec.
The privacy spec requires your DPO or legal team to review and validate the data flow mapping before we sign off on scope. We structure Session 2 so that review can happen internally between sessions, without blocking the timeline.
Feedback on this proposal. If yes:
The operational context behind this engagement.
80–90% of onboarding is manual. The same client data is entered by hand across Sumsub, Google Sheets, Elliptic, Asana, Fireblocks, and Google Drive — with no single source of truth. Every status change requires updating multiple systems. Errors compound. Reviews are delayed.
The team has already mapped what the automation should look like. The problem is not a lack of process clarity — it is the absence of an implementation layer to connect the systems that already hold the data.
What each component does and which track it belongs to.