Solutions & Services

Generative AI & LLM Data Solutions

From the building blocks of foundation models, through to the intricate fine-tuning and evaluation of large language models, the beating heart of success lies in the quality of your data.


Utilise a wide range of demographics, domain and subject matter expertise to build highly accurate, reliable and ethical data pipelines which improve the quality of training data, boost model performance, and enable safe and reliable AI.

Forge cutting-edge, domain-specific datasets with precision, by embracing LLM foundation models.

Tap into the global expertise of our domain specialists or leverage our recruitment capabilities to craft a truly tailored corpus dataset, primed for fine-tuning to your specific use case.
From technical fields to humanities subjects, including medical, legal, financial, coding and creative domains, we offer tailored assistance for diverse projects.
At Argos, our global network of linguists and domain experts covers a wide range of subjects, supporting clients in building Language Model (LLM) datasets. From technical fields to humanities subjects, including medical, legal, financial, coding and creative domains, we offer tailored assistance for diverse projects.
Our experts ensure that your dataset is enriched with relevant, high-quality data, reflecting the nuances of your chosen subject matter. With linguistic skills and domain expertise, we construct accurate and comprehensive corpora that fuel the advancement of your language models.
Let us be your trusted partner in transforming raw data into refined datasets that drive the success of your LLM projects.
Building an Ethical Data Pipeline
Our approach prioritizes ethical considerations throughout the data lifecycle, ensuring integrity and compliance at every stage. We meticulously vet data sources, implement robust privacy protocols, and adhere to industry best practices to safeguard sensitive information.
Our ethical data pipeline encompasses transparent data collection methods, stringent quality control measures, and responsible data usage policies. By prioritizing privacy, fairness, and accountability, we empower clients to navigate ethical complexities confidently while maximizing the value of their data assets.
Partner with us to build a sustainable and ethical data pipeline that aligns with your values and objectives.

At Argos, we excel in the sophisticated integration of Reinforcement Learning with Human Feedback (RLHF) techniques to refine Language Models (LLMs).

Our distinguished approach involves the seamless fusion of LLM data services with bespoke tooling, ensuring the optimal alignment of human feedback with model optimization strategies.
Through meticulous data curation, customized tooling, and task-driven refinement, we elevate the performance and accuracy of LLMs across diverse tasks and specific domains. Partner with us to leverage the power of RLHF and unlock unparalleled advancements in your LLM projects.
RLHF – Human Feedback, Scoring & Analysis
Recognizing the pivotal role of human feedback in augmenting the performance and precision of reinforcement learning models, we tailor our solutions and services to address our clients’ specific LLM requirements. From curated data collection to bespoke task design and feedback loop optimization, our offerings cater to diverse needs.
Our linguists are carefully chosen for their distinguished quality and expertise, guaranteeing that data is meticulously accurate and ethically sourced. Our state-of-the-art tooling technology is intricately crafted to enhance efficiencies across the RLHF process, encompassing response evaluation, model assessment, and performance testing.
LLM Response Correction, Quality & Relevance
Ensuring the thorough testing and evaluation of your LLM responses is pivotal for refining quality outputs. The challenge remains in scaling these activities while upholding precision. Leveraging our extensive network, we identify domain experts tailored to your requirements.
Our bespoke tooling addresses your multimodal data challenges, streamlining the evaluation and ranking processes. This enables swift determination of optimal responses, enhancing efficiency and precision in your workflow.
Retrieval Augmented Generation (RAG)
Our custom tooling is engineered to streamline the integration of retrieval mechanisms into the generation pipeline, facilitating seamless information retrieval and response generation. This ensures that responses are not only accurate but also contextually relevant and coherent.
In tandem, our platform harnesses human feedback to refine and optimize the RAG process. Expert annotators provide invaluable insights that enrich the quality and relevance of retrieved information, enhancing the overall performance of RAG models.

Carefully monitoring your LLM output is perhaps the most vital stage of development.

Mitigating risks such as bias, misinformation and hallucinations by implementing efficient guardrails is only possible with the right testing environment.
Our tooling and services are designed to support the complexities that come with this phase of development.
Red Teaming
Red-teaming involves adversarial testing and scenario simulations designed to identify vulnerabilities and weaknesses in LLM models.
Our red-teaming support includes rigorous adversarial testing, simulating real-world scenarios to identify model weaknesses. We conduct scenario simulations to assess performance under diverse conditions. Collaborating closely, we develop tooling to prioritize your specific vulnerabilities. Tailored mitigation strategies address identified weaknesses, fostering model resilience. We facilitate continuous improvement initiatives to adapt to evolving threats.
Model Benchmarking
Conducting comprehensive benchmarking against industry standards is paramount for refining your model’s performance. Harness our custom APIs and cutting-edge tooling technology to rigorously test and validate response quality, ensuring optimal outcomes for your project. Partner with us to elevate your model’s performance to industry-leading standards and drive meaningful advancements in your field.

In the realm of Generative AI development, managing data workflows presents common challenges, especially when interfacing with legacy systems and leveraging standard tooling.

With our unique baseline tech stack, we offer solutions that range from refining existing tools to crafting fully customized, tailored solutions with a shared goal to streamline efficiency across the LLM development lifecycle.
Our solutions team collaborates closely with you to grasp your deep learning and LLM objectives while evaluating your existing workflow. This enables us to provide expert recommendations tailored to your specific tooling and data requirements.
Response Quality, Evaluation and Scoring Tools
Utilise our purpose built tooling environments to create an optimized UI for collecting feedback, scoring and analysis for your LLM output. Connect to our custom API endpoints to validate and A/B test against your own or third party models, helping to aid the evaluation process in a streamlined environment. 
In-Built Quality Assurance Workflow 
We have created an advanced suite of quality assurance tools that utilize large language models to deliver comprehensive analysis of text and speech data with minimal human intervention. This innovative approach streamlines the QA process, reduces costs, and ensures the highest standards of quality. 

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