AI 革命
已然到来。
人工智能将彻底改变数据驱动的交易模式。SS&C Intralinks 凭借在 AI 领域深厚的投资积淀，提供可简化金融交易的智能应用。
更智能的交易平台
简化买方、卖方和顾问之间的协作，缩短交易完成时间。
更智能的尽职调查
为买方解锁更多信息，助其给出极具竞争力的报价。
更智能的交易洞察
提供深度分析，助力达成更多交易，实现步步为赢。
Link FAQs
How does Intralinks Manage data privacy and security?
We curate several of our own models, and customer data never leaves our environment. Our strict, multi-layer customer data security practices are continually enforced.
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How long has Intralinks been developing AI solutions?
In 2018, we began investing in developing of our own proprietary AI infrastructure and solutions.
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What large language models (LLMs) does Intralinks use?
We manage several of our own LLMs, ensuring that customer data never leaves the virtual data room (VDR). Additionally, we rigorously enforce our strict security practices regarding data tenancy
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How does Intralinks train their AI models?
We use various generally accepted methods to enhance the models we select, including techniques like few-shot learning and reinforcement learning.
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Does Intralinks use my data to train, re-train or improve their AI models?
No, we never use any customer data to train, re-train or improve our models. Your data is always safe and protected within our ecosystem.
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Does Intralinks use ChatGPT or partner with an external party?
No. Having invested in developing organic AI solutions for over five years, we do not rely on or ship data to third-party providers.
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Our commitment to AI data privacy
How does Intralinks approach AI?
As pioneers of AI-powered virtual data rooms (VDRs), we began integrating AI into our dealmaking products several years ago. Our innovative solutions streamline complex processes, delivering unparalleled efficiency and ROI.
Is my data secure?
By adhering to robust privacy practices and the highest levels of certification, your data always remains within our secure servers and is never shared externally.
What steps ensure security?
We continuously fortify our platform against unauthorized access by leveraging highly secure and auditable data centers, along with a certified private-cloud infrastructure that supports our robust AI and machine-learning stack.
How are you evolving AI?
User feedback and ongoing research and development enable us to adapt systems to evolving customer needs, ensuring we deliver an unparalleled AI experience for our global community.
我们的专家正在利用 AI 彻底改变交易方式。
Intralinks 多年来一直致力于投资 AI 和开发复杂的大型语言模型 (LLM)。体验我们最新的 AI 创新成果。
The new reality: AI and dealmaking
View Transcript
Q: Ronjohn, welcome back. Since we last spoke a year ago, what’s changed in the world of AI and dealmaking?
A: A lot has changed. Last year, we were mostly talking about AI in theoretical terms—people were exploring and trying to understand how to use it. But over the past year, we've seen a shift from exploration to true acceptance and implementation. Major financial institutions now have full teams dedicated to figuring out how to integrate AI into their workflows. The speed of adoption has been surprising. Unlike the gradual shift from physical documents to the cloud, AI has been adopted and implemented rapidly, with firms now realizing its value and putting it to work in real scenarios.
Q: Some people argue AI is a solution looking for a problem. What real dealmaking pain points is AI solving today?
A: That’s a fair critique for some technologies, but in the case of dealmaking, AI is solving significant problems—especially around document and information analysis. Deals take time because of the sheer volume of information that must be reviewed. AI started by helping summarize documents but has quickly evolved to analyzing information and generating insights that would otherwise take months to uncover. It now goes a step further by recommending decisions or highlighting areas to explore, saving time and improving the quality of decisions.
Q: For dealmakers who are still hesitant or overwhelmed, what are some tangible first steps they can take to adopt AI?
A: The first step isn’t to look for AI tools—it’s to look inward. Evaluate all internal processes and identify where inefficiencies lie. This means mapping out the entire dealmaking process from start to finish and pinpointing areas that consume the most time or resources. Once you understand your operational landscape, you can then start looking for AI solutions that target those specific gaps.
But don’t stop there—when testing AI tools, ensure they can be implemented at scale and within existing workflows. A tool that works in isolation but disrupts your system can create more problems than it solves. Integration and scalability are key to successful AI adoption.
Q: Any final thoughts on how you see AI continuing to evolve in dealmaking?
A: It’s an exciting journey. AI is already transforming how deals are processed by enhancing speed, accuracy, and decision-making. As more people adopt and experiment with these tools—and do so in a structured, strategic way—I believe we’ll uncover even more impactful use cases in the near future.
