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Platform capability 03

Chat is a useful assistant. Embedded AI is a different level again.

Chat-based AI is powerful for individual support: asking questions, drafting content, summarising information and helping users think through a problem. But finance transformation needs AI to move beyond one-off conversations.

4th Sight embeds AI into governed finance processes, where trusted data is prepared, prompts are controlled, outputs are structured, results are validated and actions can be repeated at scale.

Model flexibility

Use leading AI models inside governed finance workflows.

4th Sight can work with enterprise AI platforms and model providers, allowing finance teams to use the right model for the right process while keeping the workflow controlled, repeatable and auditable.

Alteryx One logo
Mistral AI logo
Mistral AI
Embedded AI option

Document OCR and AI extraction for invoices, supplier registers, statements and other finance documents, turning unstructured files into usable workflow data.

ChatGPT logo
ChatGPT
Embedded AI option

Enterprise-grade generative AI for commentary, classification, summarisation and process support.

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Claude
Embedded AI option

Strong reasoning and document analysis for complex finance workflow steps, reviews and exception handling.

The gap
Chat-based AI versus process-driven AI
Finance needs automation, structure, auditability and governance — not just a chat interface.
Chat-based AI
Great for ad hoc help
User-driven manual interaction
Someone has to prompt the model, copy data in and interpret the answer.
One document or one question
Chat is useful for ad hoc help, but it struggles to process operational records at scale.
Outputs not stored or reused
The answer often lives in the chat rather than becoming structured, reusable finance data.
Difficult to audit or govern
It is hard to evidence the process, control the inputs or repeat the same logic every time.
Process-driven AI
Built for scale, control and repeatability
Automated workflows
AI is embedded into a controlled process rather than used as a separate chat window.
Processes hundreds or thousands of records
Records, documents and exceptions can be processed consistently at scale.
Outputs structured and reusable
AI responses are validated, shaped and stored as data for reporting, controls and workflows.
Fully auditable and governed
The process can be scheduled, monitored, reviewed and controlled like any other finance workflow.
Chat helps the individual. Embedded AI changes the process.

Private AI platforms solve the privacy problem. The workflow solves the business problem.

Enterprise platforms can provide secure access to leading models. 4th Sight adds the operational layer that makes AI useful inside finance processes.

Private AI access

Use enterprise AI platforms such as Azure AI or Amazon Bedrock to provide controlled access to leading models.

Governance wrapper

AI usage can be embedded into permissioned, monitored and repeatable workflows.

Model flexibility

Different models can be used for different tasks, such as extraction, classification or commentary.

Repeatable process

The same prompts, controls and validation steps can be applied consistently every time.

How AI fits into the process

AI is one step inside a controlled workflow.

The surrounding process matters as much as the model. Finance data must be prepared, prompts need context, outputs need validation, and the result must feed action, reporting or review.

01
Workflow step

Data ingestion

Connect to systems, mailboxes, files, documents and foundation data.

02
Workflow step

Preparation & context

Clean, standardise and structure prompt-ready data with the right fields and context.

03
AI step

AI reasoning

Send controlled prompts to a private model for classification, extraction, commentary or review.

04
Workflow step

Output validation

Check confidence, structure the response and apply business validation rules.

05
Workflow step

Action & automation

Route exceptions, update outputs, notify users and feed dashboards or reporting packs.

Where embedded AI adds value in finance

The best AI use cases are repeatable, data-rich processes where judgement, explanation, classification or summarisation creates value.

AI-generated finance commentary
Invoice and document interpretation
Expense and PSA classification
Exception summaries
Control failure explanations
Cash matching support
Variance narratives
Supplier payment register extraction

Move from AI experiments to governed AI operations.

Start with one repeatable finance process where AI can classify, explain, extract or summarise — then wrap it in a controlled, auditable workflow.

Book an AI workflow review