--- title: "Large language models | Quantlix" description: "LLM applications and long-running agents integrated into operational software, with persistent state, authorized actions, evaluation and recovery design." canonical: "https://quantlix.com/en/services/large-language-models/" last-updated: 2026-10-09 --- Source: https://quantlix.com/en/services/large-language-models/ Language: en Description: LLM applications and long-running agents integrated into operational software, with persistent state, authorized actions, evaluation and recovery design. # Large language models LLM applications and long-running agents integrated into operational software, with persistent state, authorized actions, evaluation and recovery design. [Discuss your project](https://quantlix.com/en/contact/) [Explore the service](https://quantlix.com/en/services/large-language-models/#service-scope) ![Illustrated brain with the label LLM](https://quantlix.com/_astro/large-language-model.DQASDYeG_ZDqKP1.webp) Illustrative image. ## A clear purpose. A practical approach. ### Where this service fits Large language model engineering connects a language interface to the records, tools, and permissions a business task requires. Quantlix can scope assistants and long-running agents that retrieve information, prepare work, or execute specifically authorized actions inside existing systems. Model selection follows the workload, deployment constraints, and evaluation evidence. ### Workflow and acceptance criteria Illustrative workflow: a maintenance agent receives an equipment event, retrieves approved context, creates a permitted work request, and waits for a planner. Persistent task state records what completed and what remains open. If the connection drops after submission, recovery checks the receiving system before repeating the action. Test stale approvals, changed permissions, resource limits, and human takeover alongside answer quality. ### What to bring to discovery A language model can make complex tools easier to use when its role is clearly bounded. Quantlix designs the surrounding application as carefully as the prompts. Model fluency does not establish factual accuracy. Begin with example tasks, approved data sources and actions that require a person to confirm. ## Where we can help A focused scope, shaped around your priorities. ### Model selection Compare task quality, latency, cost and data handling. ### Application integration Connect language interfaces to authorized systems and workflows. ### Evaluation and controls Test realistic prompts, sensitive inputs and failure cases. ## A language layer for your systems Keep application permissions and validation between the model and business actions. - User request - Model gateway - Business systems - Output review ## What the work puts in your hands Agree on useful, reviewable deliverables before the work begins. - Model comparison - Application prototype - Evaluation dataset - Control specification ### Reference points These resources inform the conversation. Applicable requirements are agreed for your project. - [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) - [OWASP ASVS](https://owasp.org/projects/asvs) ## Good work starts with a shared understanding. Very small PODs bring together an expert in the specific domain and engineers selected for relevant prior industry experience. The team connects operational context with software decisions. Responsibilities, collaboration and support are agreed for each engagement. Each engagement starts with an agreed scope and a project-specific quote. [How we scope and price projects](https://quantlix.com/en/pricing/) ### Practical guides for the next decision - [How to choose an industrial AI partner](https://quantlix.com/en/blog/choose-industrial-ai-partner/) - [RAG, fine-tuning, or workflow automation?](https://quantlix.com/en/blog/rag-fine-tuning-workflow-automation/) - [A readiness checklist for long-running AI agents](https://quantlix.com/en/blog/long-running-ai-agent-readiness/) ### Start with the real problem Discuss the people, business goals and constraints behind the request. Agree on the scope and what a useful outcome looks like. ### Make the direction tangible Use working sessions, research and early drafts to explore the options. Review the tradeoffs with your team before committing to a direction. ### Work in reviewable increments Bring the agreed work into focus through regular reviews. Document the decisions, hand over the deliverables and plan any ongoing support. ## Questions, answered The practical details to consider before starting. **Can an LLM use our systems?** Yes, through defined integrations that enforce permissions and validate proposed actions. **Does the model learn from every request?** Data retention and training use depend on the provider and deployment agreement. **How do you measure quality?** Evaluate representative tasks for correctness, useful responses, latency and cost against agreed criteria. ## Connect the right services Explore the work that can support the next part of your project. [View all services](https://quantlix.com/en/services/) ![Circuit traces forming a human head on a blue background](https://quantlix.com/_astro/artificial-intelligence.z-Hurd7C_Z2l7A16.webp) ### [Artificial intelligence](https://quantlix.com/en/services/artificial-intelligence/) Industrial AI for inspection, maintenance and operational decision support. Quantlix scopes data, integration, evaluation and human review around one workflow. ![Laptop beside printed charts on a desk](https://quantlix.com/_astro/data-analytics.DsZ_dvPM_Z1g9Jo7.webp) ### [Data analytics](https://quantlix.com/en/services/data-analytics/) Quantlix builds analytics pipelines and business intelligence tools that turn operational data into defined metrics, useful reports and decision support. ![Circuit illustration with the label Generative AI](https://quantlix.com/_astro/generative-ai.w0LRubVo_28mHUX.webp) ### [Generative AI solutions](https://quantlix.com/en/services/generative-ai/) Quantlix builds generative AI workflows for drafting content and creating assets, with brand guidance, review controls and integration into publishing processes. ## Let’s talk about what needs to change. Bring your challenge, your questions and your starting point. We’ll work out the next step together. [Discuss your project](https://quantlix.com/en/contact/)