AI & Agentic Solutions
AI that does real work inside your business
We design, build, and run AI applications and agents that connect to your systems and data, from knowledge assistants to multi-step agents built on the Model Context Protocol (MCP), with the security and oversight that production use demands.
Discuss your AI use case
From AI pilot to production system
Most AI pilots stall at the same point: the model works in a demo, but it can’t reach the data and systems where the work actually happens. We build the full path, connecting models to your applications through secure integrations and MCP servers, adding guardrails and evaluation, and running the result as a supported production service.
- Use-case discovery focused on measurable business outcomes
- AI agents and assistants that work inside your existing workflows
- MCP servers and APIs that give AI controlled access to your systems
- Security, access control, and human approval built into every step
- Monitoring, evaluation, and support after go-live
What our AI & agentic solutions cover
Generative AI Applications
Assistants, copilots, and content tools built into your web and mobile applications and the workflows your teams already use.
AI Agents & Agentic Workflows
Agents that plan multi-step tasks, call tools and APIs, and hand off to people for approval, for work like ticket triage, order handling, and reporting.
MCP Servers & Integrations
Model Context Protocol servers that give AI assistants secure, permissioned access to your databases, ERP, ITSM, and internal APIs.
RAG & Knowledge Assistants
Retrieval-augmented generation over your documents, policies, and records, with source citations and access that respects existing permissions.
AI in Existing Applications
Add summarization, classification, document extraction, and natural-language search to the applications you already run, without a rebuild.
LLMOps, Evaluation & Governance
Prompt and model versioning, automated evaluation, cost and latency monitoring, and guardrails that keep AI accurate and accountable after launch.
How an AI engagement runs
Identify
A use-case workshop that ranks opportunities by value, data readiness, and risk, and picks the first one to build.
Prototype
A working prototype on your own data, with success measures agreed up front, so the decision to scale rests on evidence.
Build
Production integration with your systems through APIs and MCP servers, plus security review, evaluation, and user rollout.
Operate
Ongoing monitoring, quality checks, model updates, and support, so the solution keeps performing as your data and needs change.
Where AI agents deliver value first
Why build AI with Lantrasoft
Integration is our core strength
Over two decades of connecting applications, ERP platforms, and data, the hardest part of putting AI to work.
Model-agnostic by design
We choose the model that fits the task, cost, and data rules, and MCP-based integrations make it easier to switch later.
Governed for regulated work
Access control, audit trails, and human approval come standard. For sensitive data, SovereignReady™ keeps AI inside your boundary.
We run what we build
After launch, our Network Operations Center and support teams monitor and maintain your AI services alongside the rest of your environment.