Large Language Models

LLMs for Next-Generation Information Dominance

Achieve your mission objectives with the next evolution of language models customized to your data and workflows, in your environment

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An AI force multiplier for national security

Large Language Models (LLMs) introduce a game-changing capability for national security. At Primer, we empower analysts and operators to perform previously impossible tasks by automating their workflows with NLP. With LLMs integrated into our AI platform, we can further unlock critical parts of their daily workflows, enabling users to discover rich insights and make informed decisions at unparalleled speed.

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Intelligence and Operations

Use Cases


Speed up your intelligence cycles

Monitor news, social feeds, and reports at scale with deeper precision. Surface and summarize relevant trends across languages, understand them within their semantic context, and ask free-form questions to detect anomalies, trends, and possible adversarial intent.

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Draft comprehensive briefings with ease

Create a summary or first draft of a report in your desired format, length and tone directly from multiple inputs, including reports, presentations, social and news media, images, structured data, and more - with all sources cited.

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Stay ahead of potential threats

Streamline threat monitoring and response by rapidly gathering and analyzing data from enterprise sources and live social and news media. Evaluate scenarios and proactively address potential threats before they escalate.

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Select the best model for your mission

What Model is Right for You?

LLMs offer greater flexibility to handle a wide range of language tasks, while Standard Language Models (SLMs) may be a better fit for specialized, domain-specific and real-time needs. Both models can be fine-tuned for specific applications, making them highly adaptable to your agency’s needs.


Why Primer

  • Your Environment

    Rapidly deploy language models and high-parameter neural nets on-prem for optimal security.

  • Your Knowledge

    Integrate with your knowledge base or deploy ours with access controls and data provenance for control and confidence in your outputs.

  • Your Expertise

    Guarantee accuracy, reliability, and continual improvement with the guidance and input of human experts.

  • Your Models

    Customize large language models to meet your mission needs with our labeling platform, or let us help you.

  • Your Workflows

    Enhance your workflows and unique expertise with a fluent, collaborative and simple user interface.

  • Your Trusted Partner

    Primer is a trusted and proven AI partner for National Security agencies with deep expertise in NLP.


Critical Advantage


Question & Answering

Retrieve the answer to a question in a simple question and answer interface. Where you normally would need to read multiple documents from multiple sources, you can now retrieve what matters to your mission in seconds.

SITREP / Summarization

Generate comprehensive reports that are fully sourced and select length and format to fit your exact reporting needs. Export or share directly with stakeholders for timely insights and action.

Multilingual Translation

Read in one language and write in another language without transcription. Track evolving narratives or differences of opinion between audiences without losing language nuances.

Knowledge Base

Change the way you interact with your data by connecting to your knowledge base graph more easily in fluent, natural language and rapidly turn new information into structured, usable knowledge.

Deploy LLMs for National Security

Let us help you weigh model trade-offs and deploy the right model structure to achieve your mission.

LLMs for National Security


  • What are LLMs and why should I care?

    Large language models are the next evolution of NLP models. They are large, both in terms of the number of parameters that they use for computation, and the amount of data used to train them. LLMs can perform new writing and reading tasks previously thought to be infeasible. This is exciting because it has huge potential to help analysts and operators save significant time and effort by enhancing their intelligence and operations workflows.

  • Are LLMs different from NLP?

    NLP is a discipline focused on training machines to perform language tasks like reading, writing, summarizing, translating language, or understanding sentiment. LLMs are specific types of neural network models that are used in NLP and trained on massive amounts of text data. LLMs learn to understand language on their own by identifying patterns in text data. LLM use cases and capabilities overlap with existing NLP models. Take a look at our Primer Engines model library to get a sense of the various capabilities they cover.

  • What do LLMs do really well?

    LLMs are more versatile than standard language models at generating fluent, human-like language, having a better understanding of the semantics and nuances of human language. In addition, the models can be further trained on small unlabeled datasets and quickly tailored to specific customer needs. LLMs are sometimes called few-shot-learners, which means that they can learn from only a handful of examples provided in natural language. That level of adaptation without task-specific training is a defining characteristic of LLMs and one of their most impactful attributes.

  • What are Standard Language Models and their use cases?

    Standard language models are NLP models that are relatively smaller in size with fewer parameters and computational requirements. These models are pre-trained like LLMs but generally must be trained on specific tasks to perform at high accuracy. For example, a small language model trained to classify spam emails may not be able to generate good summaries for the email. This is because the tasks of spam email classification and email summarization require different types of language understanding that cannot be combined within the size of these smaller models.  To learn more, check out this blog.

  • What do you see as promising use cases in National Security?

    LLM capabilities include summarization of finished intelligence, querying your knowledge base or documents in natural language, and reading and writing across multiple languages. These capabilities are extremely helpful for speeding up intelligence cycles and providing comprehensive situational awareness and early warning to protect troops and assets. Now every analyst and operator can interact fluently with data in natural language, and not just developers.

  • What are some of the known limitations of LLMs?

    LLMs bring powerful new capabilities for National Security agencies, providing a potential critical advantage in certain situations. However, agencies need to balance several considerations in the context of their intended use case, including the model’s factual correctness, cost, and explainability. In certain cases, smaller models trained for specific tasks can meet your mission needs with high accuracy and in a cost-efficient manner. Primer can help you balance these considerations to determine what model is right for you.

  • Can I drop ChatGPT in my environment and expect it to work?

    No. ChatGPT is a generic application of GPT-3 LLMs from OpenAI. The application is great at “the blank page problem” and delivering tailored answers to your general questions, however it is not trained on your industry specific data corpus to serve specific mission requirements and needs.

  • I need output that I can trust. How do I manage risk?

    It is essential to have the right safeguards, monitoring tools, and corrective processes to reach and sustain high levels of performance. While the accuracy of LLMs will continue to get better, known and unknown limitations of the technology can generate inaccurate outputs.

  • I worry about cost. How expensive are these to run?

    Computational costs of running AI applications can be high, especially LLMs on enterprise applications. The costs may vary depending on the use case, the type of model used and the size of the dataset being processed. In addition to infrastructure costs, it is important to consider if you have the right talent to help deploy these. If not, we strongly recommend you find the right partner that has proven NLP expertise in National Security. Primer is ready to help you think through these things and figure out what is right for you.

  • What should I think about now to deploy this for my team?

    To successfully deploy LLMs for technological advantage, start by identifying what use cases and data you want to use them for. Consider the following: 1) Ensure that the LLMs meet strict security requirements and have necessary protocols to protect sensitive information; 2) Determine how the LLMs will integrate with existing systems, and identify potential technical challenges; 3) Estimate infrastructure cost to run LLMs on your data; 4) Develop a comprehensive training program for your team and troops to use LLMs effectively; 5) Establish a support structure for any technical issues; and 6) Define metrics to measure the effectiveness of LLMs, such as increased efficiency, improved accuracy, and reduced costs.