Custom LLM Development
Cybic builds and fine-tunes domain-specific LLMs using transformer architecture, MLOps, and CI/CD-based model deployment — tailored for legal, healthcare, finance, and enterprise operational contexts.
Cybic architects and deploys enterprise-grade Large Language Model solutions — from domain-specific LLM fine-tuning to agentic AI systems and governed deployment pipelines. Whether you operate in healthcare, finance, oil & gas, or manufacturing, our engineering-led approach transforms LLM capabilities into production-ready systems that integrate directly into your existing infrastructure and workflows.
End-to-end LLM engineering — from model creation and fine-tuning to governed deployment and intelligent automation across the enterprise.
Cybic builds and fine-tunes domain-specific LLMs using transformer architecture, MLOps, and CI/CD-based model deployment — tailored for legal, healthcare, finance, and enterprise operational contexts.
We develop enterprise GenAI copilots, LLM-powered document intelligence systems, and knowledge retrieval applications integrated into core workflows via secure, governed pipelines on AWS, Azure, and Google Cloud.
Cybic designs and deploys autonomous AI agents capable of goal-based reasoning, workflow orchestration, and multi-agent collaboration for use cases like intelligent claim processing and automated loan approvals.
We architect systems where multiple AI agents collaborate, negotiate, and execute complex tasks in parallel — enabling supply chain automation, logistics optimization, and cross-team project coordination.
Cybic connects AI platforms, LLM-powered tools, and cloud infrastructure into unified operational systems — enabling seamless data exchange between CRMs, ERPs, and data lakes via custom API development.
We embed responsible AI governance, lifecycle management, and regulatory alignment into every LLM deployment — ensuring transparency, accountability, RBAC controls, and compliance from day one.
We begin by mapping your enterprise data landscape, identifying LLM use cases, and defining governance requirements. For regulated sectors like healthcare or oil & gas, we audit compliance constraints — HIPAA, GDPR, SOC 2 — before any model design begins.
See how Cybic's LLM engineering has delivered measurable outcomes for enterprises across sectors.
We deliver working LLM systems — not slide decks. Here is what sets our engineering practice apart.
Experienced engineers architect, build, and integrate LLM systems directly — minimizing gaps between design and production deployment.
Security, RBAC, auditability, and regulatory compliance — HIPAA, GDPR, SOC 2 — are embedded at the architectural level, not added as an afterthought.
Solutions operate across cloud, hybrid, or on-prem environments on AWS, Azure, and Google Cloud — without locking your organization into rigid ecosystems.
We combine enterprise data, automation logic, and LLM models into unified operational systems — not isolated tools that create new silos.
A specialized team of engineers building real, production-grade LLM systems.
Cybic is an AI engineering company purpose-built to design and deploy enterprise-grade Large Language Model and AI systems that integrate directly into business operations. Rather than delivering strategic recommendations alone, Cybic focuses on execution — building custom LLMs, agentic AI systems, governed deployment pipelines, and intelligent automation that operate in real enterprise environments. Trusted by organizations including NVIDIA, Google, Microsoft Azure, AWS, Snowflake, and Databricks, Cybic's engineers work across healthcare, manufacturing, oil & gas, finance, retail, and the public sector — delivering LLM solutions that meet the compliance, scalability, and operational demands of each industry.
LLM engineers typically earn between $150,000 and $250,000+ annually in the United States, depending on experience, specialization, and industry. For enterprises, the more relevant question is the ROI of engaging an LLM engineering firm like Cybic — which delivers production-grade systems at a fraction of the cost and timeline of building an in-house team from scratch.
Talk to a Cybic AI engineer for a no-obligation technical consultation tailored to your use case.
Recognized expertise in deploying AI solutions on AWS infrastructure.
Validated competency in Azure-based AI and LLM deployments.
Governance, security, and ethical AI embedded into every system.
Tell us about your use case and we will scope a tailored LLM engineering engagement — focused on production deployment, governance, and measurable business outcomes.