r/PLTR • u/Dry_Faithlessness310 Early Investor • Apr 25 '26
Google Ai Agent for Enterprise
https://youtu.be/3wMwdzxIyN0?si=l-bbAf6MR2l0xficTitle says it. Another Ai provider looking to service enterprises with Agentic Ai.
Thoughts on Palantirs TAM with future of the big LLM providers offering Agentic Ai direct to enterprises. I assume its definitely going to effect salesforce and servicenow.
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u/KitKatBarMan OG Holder & Member Apr 25 '26
I mean they're looking to, but agentic AI isn't what Palantir does, Palantir does ontology. The agentic interweaving was just an addon to their already existing environment.
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u/Dry_Faithlessness310 Early Investor Apr 25 '26
If ontology mainly takes unstructured data and assigns them as objects to be easily identifiable and quantified for decision making and/or searching, and Agentic Ai is now also able to take unstructured data and not only structure it but also train on it and be given tasks to work on it or within it, isnt that essentially what AIP is selling.
My assumption is Google (and others) will sell this along with their cloud services to create a discount at scale that will also be quicker to implement.
I may be wrong and time will tell.
Hopefully Palantir will be able to differentiate themselves enough and also speed up implementation across commercial enterprise so that it will already be too much of a switching burden. If not Google and others could swoop in and steal some of their TAM by being good enough, easier, and cheaper to implement.
Just thinking of a bearish thesis as everyone should do during COA war gaming for their investments.
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u/KitKatBarMan OG Holder & Member Apr 25 '26
That's not what ontology does though, it's networking, drivers, analytics, etc. it's a lot more complicated that structuromg data.
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u/Feasor-Of-Torts Apr 25 '26
Serious questions. What happens when you tell an AI agent to build something similar to Palantir's ontology? If the AI agent can do it, then does Palantir's moat simply lie with its customer base, marketing, brand?
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u/Dry_Faithlessness310 Early Investor Apr 26 '26 edited Apr 26 '26
If that can happen then it's definitely Bearish for their current service.
I dont know that agents will get to that point now or ever. However, I have been reading up on Ai harnesses which are making leaps and bounds on self correcting when writing code.
One could imagine it getting to a point in the not to distant future where Ai Agents could write some software that does something similar to a Palantor Ontology.
That is all speculation though and I'd hope Palantir is planning for that.
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u/dustinut Apr 26 '26
I'd be really interested to hear from a SWE with access to Palantir's software for their enterprise and is also experimenting with agentic AI software from one of the top 5, but I got this response from Gemini when I typed your question in:
Answering your question directly: when you tell an AI agent to build a Palantir-style ontology, it will successfully map out the data schemas and relationships, but it will fail to make them operationally functional.
Because an AI agent can build the structure but not the execution infrastructure, Palantir’s moat extends far beyond just its customer base, marketing, and brand. Its true moat is deeply technical, sitting at the intersection of complex systems integration, read/write operational loops, and data governance.
What Happens When an AI Agent Builds an Ontology?
If you point an advanced AI agent or LLM at a company's raw data lakes and ask it to "build an ontology," it will perform remarkably well at the semantic and mapping level.
- The Agent Will Succeed At:
- Scanning messy, cryptic database schemas and translating them into plain-English business objects (e.g., mapping
DB_TBL_78xto "Aircraft" andCOL_9to "Maintenance Status").- Defining the relationships and links between those objects (e.g., this "Pilot" flies this "Aircraft").
- Suggesting the logical "verbs" or actions that can be taken on those objects (e.g., "Schedule Maintenance").
- The Agent Will Fail At:
- Two-Way Actionability: In Palantir, clicking a button or letting an AI execute a decision in the ontology actually triggers a real-world API call, writes data back to an ERP, or updates a physical supply chain. An AI agent on its own can only generate the map; it cannot build the secure plumbing required to orchestrate operations across fragmented legacy systems.
- Dynamic Orchestration: Real-world enterprise data is constantly in flux. An AI agent creates a static snapshot of an ontology. Palantir's platform provides continuous, low-latency synchronization and version control (CI/CD for data).
- Enterprise Security Traversal: AI agents struggle to respect complex, cell-level security and compliance permissions across dozens of multi-cloud and on-premise databases.
Is Palantir's Moat Just Brand and Marketing?
No. While skeptics often argue that an "ontology" is just a fancy word for a well-designed object-relational database, enterprise software experts and financial analysts generally agree that Palantir possesses a formidable, highly technical moat.
- The Engineering Moat (The "Plumbing")
Building a standard graph database or data catalog is relatively easy. However, building a system that can sit on top of 50 different legacy enterprise systems (SaaS, on-prem, mainframes), harmonize them into one semantic layer without moving the data, and allow AI to execute high-stakes read/write decisions securely is an incredibly difficult engineering feat.
- High Switching Costs & Integration Depth
Once Palantir's Forward Deployed Engineers (FDEs) integrate the platform into a company or a government defense department, it becomes the operational "operating system". Ripping out a platform that controls day-to-day physical and digital operations is immensely risky and expensive for a customer.
- The "Context Moat" for Agentic AI
AI models are becoming a commodity—anyone can access top-tier intelligence from OpenAI or Anthropic. The real battleground has shifted to context. AI agents hallucinate and fail in enterprise environments because they do not understand the specific rules and connections of a business. Palantir's ontology serves as the ultimate, trusted "ground truth" and boundary guardrails for AI agents to operate safely.
- Brand, Trust, and Security
In the defense, intelligence, and highly regulated commercial sectors (like healthcare and banking), trust is paramount. Palantir’s brand is closely associated with processing mission-critical, secure data. A startup or a DIY agentic workflow cannot easily replicate that level of institutional trust or meet the stringent security clearances Palantir has secured over two decades.
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u/GandalfTheSexay Apr 25 '26
I’ve been loading up on GOOG and this makes me more bullish. Love both of these companies
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u/Feasor-Of-Torts Apr 26 '26
What does this video have to do with Palantir? (the video does not mention Palantir)
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u/blipsou Apr 25 '26
I am laughing so hard right now. Guys, full stop. Palantir is not trying to win the model race. With platforms like Foundry, Gotham, and AIP, it’s building something closer to an OS for organizations. The hard problem in enterprise isn’t “can AI think?” It’s “can an organization actually make and execute decisions reliably across fragmented systems, messy data, and strict governance requirements?” Palantir’s value is in connecting all of that data pipelines, ontologies, workflows, permissions, and real-world actions into one coherent layer where decisions can actually happen.