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Generis & CARA: An Independent Vendor Analysis
Generis & CARA: An Independent Vendor Analysis Get your free independent analyst’s take on Generis and the CARA platform: what the company does, how CARA supports regulatory, quality, safety, and clinical programs in life sciences, and Deep Analysis’ own view on where it stands in the market for content, data,
CARA Management Centre – Life Sciences
Consistent configuration across environments The CARA Management Centre (CMC) is a standalone application that connects to your CARA instances via the REST API giving enterprise teams a single place to manage configuration, migrate data, and maintain governance across DEV, VAL, and PROD environments. Five capabilities, one application. Schedule specification exports
CARA 5.15 Feature Release – Deep Export
One action. Every document in place. Every exception accounted for. Moving large volumes of documents is rarely just a technical task. There is usually a deadline behind it, a submission, a handover, an audit. The export is the last step before something else can start. What your team needs at
Getting Value from AI : Why Life Sciences Companies Can’t Afford to Waste Time
Artificial intelligence is everywhere. Every week seems to bring another announcement promising smarter summarisation, faster drafting, or a new assistant that can shave seconds off routine tasks. For many organisations, these tools can be useful. They help individuals move faster, clear inboxes quicker, or generate a first draft more efficiently.
Turning Internal Knowledge into AI Intelligence: Why Context Is Everything
The Hidden Cost of Deploying AI Without Context There is a quiet assumption embedded in most conversations about AI adoption that deploying a large language model is, in itself, enough. Upload a document, ask a question, get an answer. The technology does the rest. This assumption is costing organisations more
The Prompt Problem: Why Uncontrolled AI Inputs Are a Compliance Risk
When AI Inputs Become a Compliance Liability When organisations evaluate AI tools, the conversation usually centres on model capability: accuracy, speed, hallucination rates. These matter. But they overlook a more operationally critical question: who controls the prompt? In generic AI platforms, prompt creation is left entirely to individual users. Everyone
Eliminating the AI “Black Box”: Traceability and Auditability
One of the most common concerns about AI in regulated environments is traceability. If AI generates an answer, how was it derived? What sources were evaluated? Can the process be audited? Many AI tools provide outputs without source visibility. This creates a “black box” scenario — unacceptable in regulatory contexts.
Security and Privacy in AI: A Regulatory Imperative
Security and Privacy in AI: A Regulatory Imperative Security is often discussed in AI conversations, but in regulated industries, it is non-negotiable.Many generic AI integrations operate through system-level access. An LLM may interact with data using elevated permissions that do not reflect individual user rights. In some models, content is
