Today we are lifting the lid on what this really means for longevity intelligence and dealmaking.
From media platform to AI-native infrastructure
For years we have been mapping the longevity landscape, tracking companies, capital flows and clinical progress across the ecosystem. That work has now crystallized into a different kind of business: an AI-native data infrastructure built specifically for aging and age-related disease.
In a world where AI is infusing every workflow, there is a simple strategic choice facing every company: become an AI business, or drift into irrelevance. Longevity.Technology has chosen the former – by hardwiring AI into how longevity data is collected, validated and turned into decisions.
Introducing DLT: Decoding Longevity Trends
DLT (Decoding Longevity Trends) is our three-stage AI system powering an investment, licensing and M&A platform for investors, founders and pharma BD. Today DLT tracks over 700 longevity and age-related disease biotechs in paid-beta; the broader datasets (800+ wider ecosystem companies and 300+ longevity clinics) will be released in 2H26.
At the core of DLT is an AI-native SaaS layer that turns raw, high-fidelity data into fact-checked, actionable intelligence – from watchlists and competitive landscapes to deal spotting and portfolio monitoring. The DLT system is already being used by clients including a top 10 Big Pharma.
How the three-stage AI system works
- Agentic AI discovery engine
Our 24/7 agentic AI continuously hunts hard-to-find, complex data on longevity companies, with a current focus on longevity and age-related disease biotech. It cycles across news, IP, clinical progress, capital flows, partnerships, people and trial updates to keep each profile live and current. - Independent LLM for fact-checking
An independent system LLM then scores and validates the agentic output against alternative sources, checking asset existence, company assignment, indications, development phase, mechanism of action and source reliability. Data is elevated into the core system once the LLM validation has been human-checked and, where necessary, directly confirmed with companies. - DLT chatbot: your interface to the graph
On top of this validated graph sits the DLT chatbot – a system-level interface that lets you interrogate the data however you choose, via both structured queries and open-ended chat. From dashboards and email alerts to deep-dive conversational analysis, the chatbot is the way users turn DLT’s machine intelligence into real-world decisions.
Specialist agents and real use cases
The DLT chatbot can be run with two specialist agents, depending on how you want to work: one that interrogates only our internally-validated system databases, and one that selectively enriches those system databases with third-party LLMs such as ChatGPT and Claude. This dual mode keeps a clean separation between benchmark-grade, fully validated intelligence and a more exploratory, enriched research mode.
You can literally ask the DLT chatbot to:
- “Run me a full management consulting style report on NLRP3, include companies and market outlook.”
- “I’m thinking of investing in company ‘X’ – provide me with an investor-grade due diligence report.”
- “List companies working on GLP‑1 agonists, company name, drug asset names, etc.”
Why DLT outpaces general LLMs
General-purpose and even scientific LLMs were not built to answer precise, transaction-grade questions about longevity biotech. DLT was.
When we benchmarked DLT against leading general and scientific LLMs on targeted queries, the difference was stark. For example, DLT surfaced 25 companies working on the mTOR pathway versus 6 for each general model, 27 biotechs in advanced aesthetics versus single digits elsewhere, and was the only system able to give a concrete number for age-related biotechs funded in the last three months.
This performance gap is the product of years of investment in building high-fidelity, domain-specific datasets: 14 longevity biotech domains (from senotherapeutics and metabolic rejuvenation to cellular reprogramming and reproductive longevity).
It is also why DLT can support workflows for pharma BD, corporate innovation, biotech VC and growth-stage biotechs – from licensing and M&A targeting to due diligence, portfolio monitoring and competitive analysis.
What you can do with DLT today
- Build and monitor watchlists with automated news and funding alerts on your target companies.
- Slice the universe of longevity biotechs by modality, hallmarks of aging, clinical stage, IP status or funding stage, with Excel export for your internal models.
- Drill down to preclinical and clinical assets with detailed targets, mechanisms, hallmarks and market context, complete with transparent confidence scores and validation provenance.
- Track leadership teams, boards and investor syndicates to understand who is really shaping each program.
Available now: book a demo
DLT is live today. You can access the platform page to explore more, or book a demo to see the DLT chatbot and dashboards in action on your own questions.
Over the coming days we will be publishing concrete examples of DLT prompts and outputs.
Disclaimer
Investing in early-stage businesses involves risks, including illiquidity, lack of dividends, loss of investment and dilution, and it should be done only as part of a diversified portfolio. First Longevity is targeted exclusively at sophisticated investors who understand these risks and make their own investment decisions. Investment opportunities have not been approved as financial promotions and are not covered by the Financial Services Compensation Scheme (FSCS) and you may not have access to the Financial Ombudsman Service (FOS). If you are in any doubt about the action you should take or the contents of any of the Financial Promotion received, you should contact your stockbroker, solicitor, accountant, bank manager or other professional adviser authorised under the Financial Services and Markets Act 2000, who specialises in advising on bonds, shares and other securities, including unlisted securities.
Past performance is not a reliable indicator of future performance. You should not rely on any past performance as a guarantee of future investment performance. Tax relief depends on an individual’s circumstances and may change in the future. In addition, the availability of tax relief depends on the company invested in maintaining its qualifying status.
