Industry — Finance
Close the month without the manual grind.
Finance teams spend their days keying invoices, chasing reconciliations and rebuilding the same reports. The work is repetitive, deadline-bound, and the data is far too sensitive to paste into a public AI tool.
Business value
Give the finance team time back.
The aim is not a generic chatbot. It is a controlled operating assistant that removes repetitive work while keeping finance accountable.
Hours returned
Reduce time spent finding documents, matching transactions and rebuilding recurring reports.
Lower operating cost
Handle more volume without adding the same amount of manual processing effort.
Fewer manual errors
Apply the same checks every time, surface exceptions and retain human approval for record changes.
Exact time and cost savings are measured against your current process during discovery — not assumed in advance.
What it does
Concrete work the assistant takes off your team.
Invoice & payables processing
Extract line items, match to purchase orders, flag exceptions and route for approval — with a human sign-off before anything posts.
Bank & intercompany reconciliation
Match transactions across accounts and entities, and surface only the breaks that need a human decision.
Recurring management reporting
Assemble the monthly reporting pack from your own ledger data, in the same format every period.
Receivables follow-up
Track ageing, draft follow-up correspondence and keep a record of what was sent to whom.
Questions from your own records
Ask plain-language questions of your financial data and get answers grounded in your ledger, not a generic model's guess.
Contract & term extraction
Pull payment terms, renewal dates and obligations out of agreements into a structured, searchable view.
From question to controlled action
How it works in your finance team.
Staff use a familiar, approved interface. The assistant follows permissions, grounds every answer in approved sources, and pauses for human approval before it changes a record.
- 1
Ask
A finance user asks a question or starts a task in the approved interface.
- 2
Check permission
The assistant applies the user's team and data-access rules before retrieving anything.
- 3
Read approved sources
It gathers the relevant records from systems such as Odoo and approved document stores.
- 4
Answer or prepare an action
It returns a grounded result, records the request, and asks for approval before any write-back.
What Manciti deploys
- Private AI model and retrieval index
- Knowledge layer for finance policies and documents
- Workflow coordinator with human approval gates
- Connectors to approved ERP and document systems
- Role-based access controls and audit services
- Customer-controlled server and ongoing local support
Choose the interface boundary
Fully isolated internal interface
For zero external message transport. The entire interaction remains inside the approved environment.
Microsoft Teams integration
For a familiar employee experience. Messages and replies follow your Microsoft 365 tenant's residency, retention and DLP configuration.
Data sovereignty
Your finance AI core stays in your controlled environment
Ledgers, payroll, customer accounts and contracts remain in approved source systems. The model, retrieval index, workflow service and audit logs run on infrastructure you control; they are not sent to an external AI-model provider.
Choose the fully isolated internal interface for zero external message transport. If Teams is selected, user messages and assistant replies are handled under your Microsoft 365 tenant's residency, retention and DLP configuration.
Every request and action is written to an audit log, and any step that changes a record requires human approval — which is what a finance function needs to stay auditable.
How the private deployment worksStart with evidence
Finance AI Discovery
2–3 weeksWe start with one finance sub-team and one high-value workflow, then prove the business case using your process, volumes and controls.
Discuss a finance workflowYou receive
- A mapped current-state workflow and control requirements
- A working demonstration using approved sample data
- A business case based on your time, volume and error rates
- A fixed-price scope for the production build
There is no commitment beyond discovery. If the numbers do not support a build, you still leave with a clear process and business case.
AI for Finance Teams
Manciti will scope a pilot on one high-value use case before you commit to anything larger.