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Llama integration and customization services

We deliver end-to-end integration of Llama models into your existing systems. Our team develops Llama-powered applications, including API, RAG pipelines, fine-tuning, and secure deployment.

llama integration and customication services

We developed AI tool for contract risk and compliance analysis
We integrated a Large Language Model (Bielik) to provide accurate legal insights.
Our solution processes contracts extracts key details, and highlights risks.
Our AI chatbot answers legal questions using a fine-tuned knowledge base.
We built and deployed an AI Agent for Credit Agricole bank
We developed and deployed a fully operational AI Agent in Credit Agricole.
Our team ensures AI compliance with strict (financial) regulations.
The AI Agent automates simple inquiries and directs complex ones to the right teams.

End-to-end development

Our comprehensive Llama integration and development services

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Llama API Integration

We develop middleware to connect Llama API with your existing systems. Our solutions ensure secure, real-time data exchange and full compatibility with your enterprise infrastructure.
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Domain-specific AI Agents development

We create AI agents powered by Llama for finance, healthcare, and legal industries. These agents handle multi-turn dialogues, process complex queries, and provide highly contextual responses optimized for specific industry applications.
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Multimodal Llama applications

We develop AI solutions that combine LLaMA 3.2’s vision capabilities with text-based models. These applications process images and documents alongside text to generate context-aware responses and assist in tasks like automated document review and data extraction.
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Llama optimization & fine-tuning

We fine-tune and optimize Llama models to ensure efficiency, scalability, and cost-effectiveness. We fine-tune Llama using LoRA/QLoRA techniques with proprietary datasets and optimize it for deployment in constrained environments (under 16GB VRAM).
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Data pipeline engineering

We build data pipelines that prepare and feed data into Llama models. Our process includes data cleaning, transformation, and integration from multiple sources, ensuring high-quality inputs that optimize model performance.
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Llama deployment

We provide secure on-premise deployments with air-gapped infrastructure for industries that require strict data control. We also build cloud or hybrid architectures to balance scalability and security. Our solutions meet GDPR, HIPAA, and other industry regulations.

Our Generative AI development expertise


330
IT experts on board
11
awards and recognitions
for our GenAI solutions
236
clients served in custom development

We provide complete support for Llama integration and deployment

What we cover in Llama integration and customization services


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    1. Discovery & Architecture design

    We assess your infrastructure, security needs, and technical requirements to design the optimal Llama deployment strategy.

    This includes:

    • Evaluating GPU compatibility (NVIDIA support, CUDA versions) and token throughput for large-context models.
    • Conducting a data security assessment to ensure GDPR/HIPAA compliance.
    • Creating a solution blueprint, including hybrid cloud/on-prem model serving and customization roadmaps.
  • Gen AI PoC development

    2. Proof-of-Concept development

    We deliver a functional prototype to test Llama’s capabilities in real-world conditions.

    This includes:

    • Implementing a RAG-powered knowledge retrieval system for enterprise applications.
    • Developing an executable demo with performance benchmarking.
    • Comparing model outputs against baseline models to optimize for accuracy and efficiency.
  • Self-hosted LLM development - Custom LLM selection & fine-tuning

    3. Data pipeline engineering

    We build high-performance data pipelines to prepare and feed structured data into Llama models.

    This includes:

    • Chunking strategies to enhance retrieval efficiency.
    • Automated PII redaction for compliance with data security policies.
    • Multi-format data ingestion, supporting PDFs, databases, and APIs for comprehensive knowledge integration.
  • Self-hosted LLM development - Training and optimizing

    4. Model optimization phase

    We fine-tune and optimize Llama for performance, cost efficiency, and deployment feasibility.

    This includes:

    • Quantization (with FP8 precision and GPTQ), reducing VRAM usage for deployments under 16GB.
    • Speed optimization using TensorRT-LLM and vLLM.
    • Accuracy improvements through RAG enhancement and RLHF.
  • Self-hosted LLM development - Security & compliance

    5. Security hardening

    We implement advanced security measures to ensure the integrity and compliance of Llama deployments.

    This includes:

    • Model weight encryption (AES-256) and runtime integrity checks to prevent unauthorized access.
    • Role-Based Access Control (RBAC) integration with Azure AD for enterprise authentication.
    • Audit logging and compliance tracking for SOC 2 security standards.
  • Self-hosted LLM development - API & interface development

    6. Deployment & Scaling

    We deploy Llama on-premise, in the cloud, or in hybrid environments with auto-scaling capabilities.

    This includes:

    • Containerized deployment via Docker and Kubernetes, supporting high-availability scaling.
    • Optimized inference infrastructure (e.g. by leveraging NVIDIA Triton Inference Server for real-time processing).
    • Cloud cost optimization, using spot instances for fine-tuning and serverless model serving.
  • AI and LLM Agent development - Security, compliance & guardrails

    7. Continuous improvement

    We provide ongoing monitoring, updates, and performance tuning to keep Llama running at peak efficiency.

    This includes:

    • Real-time hallucination detection using entropy-based thresholding.
    • Model drift alerts and usage analytics dashboards to track AI performance.
    • Regular updates (e.g. including adapter swapping for new capabilities and security patches).

Practical applications in fintech, finance, and consulting

Some of the top Llama use cases

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Customer Service automation

Real-time query resolution via chatbots integrated into helpdesk systems for efficient support.
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Enterprise knowledge management

Internal tools for document summarization and policy search using embeddings for quick retrieval.
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Finance recommendations

Real-time insights for sales agents to recommend tailored financial products and services.
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Fraud detection support

Monitoring transactions for irregularities with AI alerts to enhance security measures.

They trusted our expertise


cresit agricole logo
Dekra
Carefleet

Tools and technologies

Our AI tech stack for Llama integration


Llama Services

Llama 3.1 / 3.2 / 3.3 Models Embedding APIs (for semantic search) RAG (Retrieval-Augmented Generation) Custom Fine-Tuning APIs Agent-based Applications

NLP Tools

spaCy NLTK Gensim Transformers (Hugging Face) FastText

Chatbot Frameworks

Rasa Dialogflow Microsoft Bot Framework BotPress Custom Llama Agents

Deployment

AWS Azure Google Cloud Kubernetes Docker

Monitoring & Analytics

Prometheus Grafana Elasticsearch Datadog Llama Stack Monitoring Tools

We build effective AI apps

Llama stack integration and orchestration

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Llama stack integration

We integrate Llama into your infrastructure with prebuilt connectors for PyTorch, TensorRT-LLM, and vLLM to ensure efficient deployment and compatibility with your existing AI stack.

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Observability suite

We provide real-time monitoring tools to detect model drift, hallucinations, and performance issues. Our observability solutions help maintain AI reliability and optimize ongoing performance.

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Multi-LLM orchestration

We can implement fallback mechanisms that combine Llama with Claude, GPT-4, and other LLMs for enhanced accuracy and resilience. This ensures uninterrupted responses and improved AI decision-making.

Testimonial

What our clients say

By automating certain customer interactions, bank employees are provided with a prepared “semi-product”, which enables them to dedicate more time to personalizing and empathizing with customer communication, and thus taking even better care of their needs.

Katarzyna Tomczyk – Czykier
Director of the Innovation and Digitization Division – Retail Banking

Why choose us

Llama integration company

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Advanced integration architecture

Our Llama integrations are built with robust middleware, API optimization, and advanced techniques like embedding-based semantic search and multi-turn dialogue management.
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Industry standards compliance

We maintain the highest levels of security and data protection, holding ISO 27001 certification. Our solutions are fully compliant with industry standards (e.g. GDPR, CCPA).
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Deep domain knowledge

We have extensive experience in banking and finance. We can navigate the complexities of compliance and security in regulated industries.

Get in touch

Let’s talk


Book 1-on-1 consultation 

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Grzegorz Motriuk

Head of Sales | Application Development

Our consultant is at your disposal from 9 AM to 5 PM CET working days from Monday to Friday for any additional questions.