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Fig vs. Palantir
Fig gives companies every frontier model and the best open-weight models, a full set of AI primitives from voice agents to vision and computer use, and models of their own trained with every method that moves cost and quality. Engagements start with a pilot that puts real work into production on your systems.
Fig vs. Palantir, in short
Fig is built for commercial companies and for the frontier. Palantir was built for defense, intelligence and government, and its 2026 strategy centers on open-weight models fine-tuned inside AIP, which its leadership argues can solve most problems below the frontier. Fig runs every lab's newest models alongside open-weight models, offers AI primitives across voice, vision, image, video, research and computer use, and trains models with supervised fine-tuning, preference tuning, reinforcement learning and distillation, where Palantir's customization is LoRA fine-tuning on Ontology traces. Fig engagements start with a pilot in production; Palantir's start with a one to five day bootcamp.
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| Feature | Fig | Palantir |
|---|---|---|
| Built for | Commercial companies of every size, self-serve or hands-on. | Defense, intelligence and government, still much of its business. |
| Models | Every lab's newest frontier models plus the best open-weight models, routed to the right one for each task. | Strategy centered on open-weight models fine-tuned in AIP, below the frontier. |
| AI primitives | Voice agents, vision, image, video, music, deep research, computer use, coding and documents. | Language-model logic and agents over the Ontology. |
| Model training | Supervised fine-tuning, preference tuning, reinforcement learning and distillation, chosen per task. | LoRA fine-tuning of open-weight models on Ontology traces. |
| How it starts | A pilot: Fig's engineers put one workflow into production on your systems, measured against a baseline. | AIP Bootcamps: one to five day workshops where your engineers prototype a use case. |
| Who uses it | Every employee in Slack, WhatsApp, Telegram, desktop, mobile and web, plus your customers through websites, portals, phone and messaging. | Analysts and operators in apps built on Workshop. |
Included Partial or with conditions Not offered
Palantir was built for defense and intelligence agencies, and government is still much of its business: its US government revenue alone was $953 million in Q3 2026. Fig is built for commercial companies and the work they compete on, serving customers, running operations and building products, at companies of every size, self-serve or with Fig's engineers alongside.
Palantir's chief technology officer argues that most valuable problems can be solved below the frontier, and its 2026 platform centers on open-weight models fine-tuned inside AIP. Fig works at the frontier: every lab's newest models as they ship, the best open-weight models for cost and speed, and a full set of AI primitives, including voice agents that handle calls, vision, image and video generation, deep research, computer use and coding, so a system can use whatever the work needs.
Palantir's model customization is LoRA fine-tuning of open-weight models on traces from its Ontology. Fig trains with the full range of methods, supervised fine-tuning, preference tuning, reinforcement learning and distillation, and picks the method each task needs, so a company's own models reach frontier-level quality at a fraction of the cost and latency. Every model is tested on the company's own cases before it does real work.
Palantir engagements start with AIP Bootcamps, one to five day workshops in which the customer's own engineers prototype a use case. Fig engagements start with a pilot: Fig's engineers put one high-value workflow into production on the company's systems, measure it against a baseline, and expand from there.
Commercial companies that want AI built at the frontier: every lab's newest models and the best open-weight models, voice, vision and the full range of AI primitives, models trained with every method that improves cost and quality, and a pilot that reaches production on their own systems.
Fig is built for commercial companies and for the frontier; Palantir was built for defense, intelligence and government. Fig runs every lab's newest models alongside open-weight models, offers AI primitives across voice, vision, image, video, research and computer use, and trains models with supervised fine-tuning, preference tuning, reinforcement learning and distillation. Fig engagements start with a pilot in production rather than a bootcamp.
Yes. Fig is built for commercial companies of every size, with every frontier and open-weight model, a full set of AI primitives, model training with every major method, and engineers who put a first workflow into production in a pilot.
Fig chooses the method each task needs: supervised fine-tuning to teach format and behavior, preference tuning for judgment and taste, reinforcement learning for skills the base model lacks, and distillation to make a model smaller, faster and cheaper. Each model is tested on the company's own cases before it serves real work.
With a pilot. Fig's engineers put one high-value workflow into production on the company's own systems, measure it against a baseline, and expand from there.
Every frontier lab's newest models and the best open-weight models, routed to the right one for each task, plus models Fig trains on the company's own data.
Bring your most important workflow. We'll show it running on Fig with your data, your rules and your choice of models.
Dream big, build fast, and grow far with Fig