AI Process Audit
The AI process audit is the foundational step that determines which workflows are worth automating. For a 51-200 person healthcare company in the UK, the audit maps the contract review process, measures baseline cycle time (e.g., 12 hours per contract) and error rate (e.g., 8% missed clauses), and selects the highest-impact workflow for a 4-week pilot. This ensures the AI investment targets a measurable bottleneck rather than a low-value task. The audit also identifies integration points with existing systems, such as the document management system and CRM, to ensure the AI assistant plugs into the company’s current infrastructure rather than replacing it. By grounding the pilot in concrete metrics, the audit provides a clear baseline against which the AI’s performance can be measured, which is critical for demonstrating ROI to stakeholders and ensuring the project aligns with the company’s ISO 27001 compliance requirements.
Anthropic Claude API
The Anthropic Claude API is a large language model service that Forfis uses for high-quality text generation and classification tasks. In the contract review scenario, Claude handles the semantic analysis of legal clauses and drafting of redlines. Because the data is sensitive, the API calls are routed through a custom REST gateway that enforces ISO 27001 logging and access controls, ensuring that no raw contract data is stored on Anthropic’s servers beyond the inference window. The model-agnostic architecture allows Forfis to switch to open-weight models on the client’s own hardware if the data cannot leave the building, but for most contract review tasks, the Claude API provides the best balance of quality and cost. The API’s context window of 200,000 tokens allows the model to process entire contracts in a single pass, which is critical for maintaining context across complex legal documents.
Retrieval-Augmented Knowledge Assistant
A retrieval-augmented knowledge assistant retrieves relevant passages from a company’s internal documents—contracts, SOPs, CRM records—and uses them to ground an LLM’s response. In a UK healthcare contract review, the assistant pulls the specific liability clause from a 2023 supplier agreement and flags it against the current ISO 27001 Annex A.8.25 requirements, reducing manual search time from 45 minutes to under 3 minutes per clause. The retrieval index is built from the company’s document management system and updated weekly to include new contracts and policy changes. This approach ensures that the AI’s responses are grounded in the company’s actual data rather than general knowledge, which is critical for legal and compliance tasks where accuracy is paramount. The assistant also logs every retrieval and response, providing an audit trail that satisfies ISO 27001 A.8.15 logging requirements.
ISO 27001
ISO 27001 is an international standard for information security management systems. For a 51-200 person UK healthcare company, it mandates risk-based controls for data handling, access, and incident response. When deploying an AI contract assistant, the company must ensure the model’s data pipeline complies with Annex A.8.25 (secure development) and A.8.15 (logging), which is why the architecture uses custom REST APIs to keep PHI and contract data within the client’s VPC rather than sending it to a third-party SaaS. The standard also requires that the company maintains a risk assessment that includes the AI system, which means the AI’s data flow, access controls, and incident response procedures must be documented and reviewed annually. For a company in the healthcare sector, ISO 27001 compliance is not optional—it is a prerequisite for many contracts with NHS trusts and private healthcare providers, making it a critical consideration in the AI deployment strategy.
Custom REST API and Webhooks
A custom REST API and webhooks integration allows the AI assistant to pull contract data from the company’s existing document management system and push reviewed drafts back to the legal team’s workflow. Webhooks trigger the AI review when a new contract is uploaded, and the REST API returns the annotated PDF and a JSON summary of flagged clauses. This avoids replacing the existing DMS and keeps the integration within the company’s ISO 27001 scope. The API is designed to be idempotent, meaning that if a webhook is retried, the AI review is not duplicated, which is critical for maintaining data integrity. The integration also includes rate limiting and authentication to ensure that the AI system is not abused or overwhelmed by a sudden spike in contract uploads. By using the company’s existing APIs rather than building a new system, the integration reduces the risk of data loss and ensures that the AI assistant fits seamlessly into the company’s current workflow.
Managed AI Operations
Managed AI operations is a delivery model where the vendor handles ongoing monitoring, model updates, and performance tuning after the initial pilot. For a healthcare company, this means Forfis tracks the contract assistant’s accuracy weekly, adjusts the retrieval index when new contract templates are added, and ensures the system remains compliant with ISO 27001 as the company’s security posture evolves. This removes the need for the client to hire a dedicated AI engineer, which is critical for a 51-200 person company that may not have the budget or expertise to maintain an AI system in-house. The managed operations contract includes a service level agreement (SLA) that specifies the maximum downtime (e.g., 4 hours per month) and the response time for critical issues (e.g., 2 hours). By outsourcing the ongoing maintenance, the company can focus on its core business while ensuring that the AI system continues to deliver value and remain compliant.
Human-in-the-Loop
Human-in-the-loop (HITL) is a design pattern where the AI drafts or classifies, but a human approves any action that touches money, health data, or contracts. In the contract review scenario, the AI flags clauses and suggests redlines, but a legal reviewer must approve the final version before it is sent to the counterparty. This ensures that the AI’s output is auditable and that the company retains legal accountability, which is critical for ISO 27001 compliance. The HITL workflow is designed to minimize the time the human spends on the task—the AI pre-filters the contract and highlights only the clauses that require attention, reducing the reviewer’s workload from 12 hours to 3 hours per contract. The system also logs every human decision, providing an audit trail that can be used for compliance reporting and continuous improvement. By keeping the human in the loop, the company ensures that the AI is a tool that augments human expertise rather than replacing it, which is essential for maintaining trust and accountability in a regulated industry.
Leave a Reply