# Fig vs. Palantir

> Built for commercial companies, at the frontier.

- Canonical: https://hellofig.io/alternatives/palantir
- All comparisons: https://hellofig.io/alternatives.md
- About Fig: https://hellofig.io/fig.md

**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.

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.

## At a glance

| | Fig | Palantir |
|---|---|---|
| Built for | Commercial companies of every size, self-serve or hands-on. | Partial: 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. | Partial: 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. | Partial: Language-model logic and agents over the Ontology. |
| Model training | Supervised fine-tuning, preference tuning, reinforcement learning and distillation, chosen per task. | Partial: 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. | Partial: 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. | Partial: Analysts and operators in apps built on Workshop. |

## Built for commercial companies

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.

## Built at the frontier

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.

## Training that pushes cost and quality

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.

## A pilot in production

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.

## Who Fig is for

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.

## Questions

### What is the difference between Fig and Palantir?

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.

### Is Fig an alternative to Palantir for commercial companies?

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.

### How does Fig train custom models?

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.

### How does a Fig engagement start?

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.

### Which AI models does Fig use?

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.