Your clients trust you with their financial data. FlowLeap is built as a controlled processing and workflow layer - AWS-hosted, encrypted, access-scoped, with model inference routed through Amazon Bedrock and human approval for high-impact actions. Here is exactly how it works.
The controls expected from a professional external software provider - applied from the moment data enters a workflow to the moment a connection is revoked.
Production client-data workflows run in the AWS Europe (Ireland) region, eu-west-1. Client data remains inside the FlowLeap AWS-hosted environment and the approved inference route - it is not copied into public tools.
Client data is encrypted in transit and at rest, using AWS-managed, KMS-backed encryption. Older, insecure transport protocols are not used.
OAuth refresh tokens, API keys, credentials, and connection secrets are held in approved production secret stores and protected by AWS KMS-backed controls - separated from the data they unlock.
Access to mailboxes, document stores, PDFs, ledgers, and payroll sources is scoped to the approved clients, books, folders, and workflow purposes. Access is never treated as permission to process everything in a connected system.
The default starting position is read-only. Sending email, changing ledgers, releasing payroll, or submitting statutory records stays disabled unless a named write capability and its approval path are separately agreed.
Data is separated by firm, client, book, source connection, user, and workflow scope - enforced by database-level row access controls (or a documented datastore isolation control) plus application-level checks.
Operational logs are built around metadata and redacted by default. Any content-bearing logs, prompts, outputs, or support records are treated as client data. Model invocation logging is disabled unless agreed for a defined purpose.
Revocation disables the relevant source connection, stops new processing, invalidates tokens where supported, and records completion. Retention and offboarding follow the approach agreed in the engagement.
When FlowLeap uses AI, it means model inference as one controlled step inside a workflow - not a public chatbot with open-ended access to your data.
Standard client-data workflows run model inference through Amazon Bedrock, AWS's managed service for foundation models behind an enterprise service boundary. Any Anthropic models used are invoked as Bedrock-hosted models.
Client data is not sent to consumer Claude.ai or ChatGPT, nor to any direct public model API. Standard workflows also do not use Cross-Region or global Bedrock inference profiles.
Your data is used to run tasks, not to train models. Client data is not used to train base models through the approved Bedrock route, and is not used for cross-client model training, fine-tuning, or customisation.
The workflow sends only the task-specific context a step needs. The model does not receive independent or unrestricted access to your mailboxes, document stores, ledgers, or payroll systems.
Model output is a reviewable work item - an extraction, classification, summary, or draft linked to its source references - that your team can accept, correct, or reject. It is never treated as a final answer on its own.
External, irreversible, ledger-changing, payroll-impacting, or client-facing actions pass through a human approval gate by default before anything is executed.
FlowLeap acts as a data processor - an operator - on behalf of your firm. Your firm retains data ownership and control at all times. We process your clients' data only to deliver the services you've contracted us to provide - never for advertising, model training, or sale to third parties.
South African firms - We generally act as an operator under POPIA, processing personal information on your firm's instructions. The production environment is hosted in AWS Ireland (eu-west-1), so for South African personal information this is a cross-border arrangement: the engagement records the operator role, the POPIA section 72 transfer basis, approved sub-operators (such as AWS), security obligations, retention, and incident-notification position.
European firms - Our Data Processing Agreement (DPA) covers the required GDPR obligations for EU-based firms and is compatible with UK GDPR for firms in the United Kingdom.
Each firm remains responsible for confirming the appropriate lawful basis and client notices for the underlying client data. Subject access, deletion, and portability requests are supported under both POPIA and GDPR.
You own your data. Always. We have no right to use your clients' financial data beyond service delivery.
Your firm's data is never used to train AI models that serve other customers. Your workflows remain yours.
On termination, your data is removed in line with the agreed retention and offboarding process, with completion recorded.
Approved sub-processors (such as AWS) are recorded in the engagement, with their role and service layer defined.
Our AI colleagues are built with explicit boundaries - and designed to escalate rather than guess.
AI colleagues never send client communications without human review and approval. Your team controls what goes out - always.
When an AI colleague encounters ambiguity, complexity, or an exception it hasn't been trained on, it flags the item for human review - it does not attempt to resolve it alone.
AI colleagues operate within strictly defined workflows. They do not have access to systems, data, or actions outside their configured scope. Permissions are explicit and auditable.
Every action is recorded with its workflow context and source references. Your team can review exactly what was done, why, and when - at any point in time.
We're happy to discuss specific requirements, provide the IT-review overview and operator agreement, or work through your firm's procurement process.