Choosing the process
Together we pick the process that repeats most often, has a clear definition of "done" and has its data in your systems. We define what the AI does on its own and what it does only after a person approves.
Applications with financial statements and an Experian query, asset documents from the vehicle registry, insurance policies, contracts signed via DocuSign and payment reminders from Soft4Leasing: in a leasing company this is a constant flow of documents. We implement private AI that extracts the data, cross-checks it and prepares drafts, while a person makes the credit decision. Everything is logged, in line with GDPR and DORA.
Built for ISO 27001NIS2 DORA
A leasing account manager's day starts in the inbox: the application, two years of financial statements, bank statements, a vehicle or equipment quote with VIN and price, an appraiser's report, an insurance policy. All of it has to be keyed into the application record in Soft4Leasing or Business Central, an Experian report has to be requested separately, and the figures and details have to be checked against each other. The VIN is verified with the vehicle registry, the contract and annexes are prepared from a template, sent out for signature via DocuSign, and the customer, who is already asking about the schedule, needs an answer. Meanwhile customer service answers the same questions about balances and confirmation letters, and the collections team writes reminders by hand from the Business Central overdue report. Every retyping costs an extra hour and leaves room for an error in the contract.
AI takes over the document work: it extracts the application attachments into Soft4Leasing or Business Central fields and adds a summary of the Experian report, cross-checks the asset documents against vehicle registry data and the insurance policy against the contract, prepares a draft of the contract and annexes from your template and, after approval, sends it for signature via DocuSign, answers the customer after an identity check, and drafts reminders and payment arrangement letters. We implement with Claude, Microsoft 365 Copilot and ChatGPT, and for customer and financial data we use private AI: models in the MDP CLOUD GPU cloud in Lithuania (EU) or Amazon Bedrock in an EU region. We connect to Soft4Leasing, Business Central and other systems through an API, a file export or an e-mail flow, depending on your version. The first step is role-based access, EU data residency, a log in line with GDPR and DORA, and a clear boundary: AI prepares the credit committee file, but a person makes the credit decision and the risk assessment.
The 5 solutions we implement most often in this industry. Each one starts with a single process, has a human approval step and is measured.
From the application and its attachments (balance sheet, profit and loss statement, bank statements, an asset quote with VIN or serial number), a private model extracts the fields into the Soft4Leasing or Business Central application record as a draft, adds a summary of the Experian report, cross-checks the amounts between documents and flags missing or mismatched data. The risk analyst receives a prepared record and makes the decision.
We implement: Document recognition on Amazon Bedrock in an EU region + Soft4Leasing or Business Central and Experian integration
After the credit decision, AI takes the data in Soft4Leasing (customer, asset, schedule, interest, insurance terms) and fills in the contract template and annexes approved by your lawyers, flagging non-standard terms that need review. The account manager and the lawyer approve the document, and only then is it sent for signature via DocuSign.
We implement: Claude via API + Soft4Leasing data, templates from SharePoint, sending via DocuSign
After login to the self-service portal or confirmation by e-mail, the assistant answers the customer about the payment schedule, balance, next instalment and early settlement amount from Soft4Leasing or Business Central, and prepares balance confirmation letters and invoice copies. Requests to change the contract, defer a payment or dispute something are passed to the account manager with a summary and the contract number.
We implement: Claude assistant + read-only access to Soft4Leasing or Business Central and the self-service portal
A private model cross-checks the appraiser's report, the seller's invoice, vehicle registry data and the insurance policy against each other and against the contract in Soft4Leasing: VIN, owner, value, insured amount, beneficiary and expiry date. Mismatches and policies about to expire go to a list for the responsible employee to approve.
We implement: Private model on Amazon Bedrock in an EU region + vehicle registry data and Soft4Leasing contracts
Every morning, based on overdue payment data from Business Central, the agent prepares drafts of reminders, payment arrangement letters and warnings according to your stages and tone, and a collections specialist reviews and approves sending. Customers with a dispute or an arrangement are separated out and kept out of the automated flow, and a referral to Experian is decided by a person only.
We implement: Copilot Studio agent + Power Automate flow from Business Central
From the first conversation to a working solution, with measurement and ongoing support.
Together we pick the process that repeats most often, has a clear definition of "done" and has its data in your systems. We define what the AI does on its own and what it does only after a person approves.
We put access to files and systems in order, give the AI its own identity with the least privileges it needs, turn on an action log and choose where the model runs: your Microsoft 365, Amazon Bedrock in an EU region or our GPU cloud in Lithuania (EU).
We build the solution with Copilot, Claude or ChatGPT, whichever fits the task, connect it to your systems and test it on historical documents and enquiries until accuracy reaches the agreed threshold.
We launch with a person in the loop, review the logs and exceptions and adjust the rules. Once the first process runs reliably, we move on to the next one on the list.
These solutions are a starting point for a conversation, not a complete list. Tell us which processes repeat in your company, and in one conversation we will tell you what is worth handing to AI and what is not.
No. AI extracts and cross-checks the documents and prepares the credit committee file in Soft4Leasing or Business Central with notes and an Experian summary, but the financing decision, the terms and the risk assessment are made by your employees, and their approval is written to the log. This keeps the accountability and traceability that your regulator and internal audit require.
Yes, but we choose the integration method after a check. Soft4Leasing runs on Business Central, so we usually connect through the Business Central API and Power Automate connectors, and for older versions through a file export or an e-mail flow. We pull vehicle registry and Experian data through the contracts and access you already have, and DocuSign through its API. We have no official partnership with these systems and do not claim one.
No. For customer and financial data we use private AI: models in the MDP CLOUD GPU cloud in Lithuania (EU) or Amazon Bedrock in an EU region, where data is not used for training and does not leave the EU. We prepare usage rules for employees, and we manage access to Soft4Leasing and Business Central through Microsoft Entra ID by role.
Orders arrive as e-mails and PDFs, and someone keys them into Business Central or SAP Business One by hand.
AI where data cannot leave the organisation: open models in our GPU cloud in Lithuania (EU), Claude through Amazon Bedrock in an EU region, or a…
Repetitive tasks that a person does today can run by themselves, more accurately and without waiting.
This service is delivered by specialists with valid international certifications. Their expertise is confirmed by independent organisations, not by us.
AI systems are deployed with protection against data leakage and model abuse.
The AI security programme and its controls are managed following the ISACA methodology.
AI risks are identified and managed like any other IT risk.
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