Enterprises
Integrate AI into existing systems while working within enterprise security, compliance, infrastructure, and procurement requirements.
Build production-ready AI agents that autonomously reason, plan, and execute across your business systems
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A chatbot answers questions. An agent completes tasks. Primotech's agent development work covers the full path from a single task-specific agent to coordinated multi-agent systems that plan, use tools, and hand off work to your team when a decision needs a human. We build agents around your actual workflows and systems, not a demo environment that behaves differently once it hits production.
Task-specific agents built around a defined goal, toolset, and success criteria—suited for focused workflows like research, triage, or data entry.
What’s included: Goal and scope definition, tool selection, prompt and reasoning design, testing, and deployment.
Coordinated agent systems that divide complex work across specialized agents, communicating through standards like MCP and A2A.
What’s included: Agent role design, task routing, inter-agent communication, shared memory, and orchestration logic.
Agents connected to your CRMs, databases, internal APIs, and business systems so they can take action—not just generate a response.
What’s included: API and system integration, authentication and permissions, action logging, and error handling.
Short-term and long-term memory architectures that let agents retain context across sessions, tasks, and conversations.
What’s included: Memory architecture, context management, retrieval integration, and reasoning-chain design.
Approval workflows, escalation paths, and monitoring that keep autonomous action within limits your team defines.
What’s included: Permission scoping, human-in-the-loop checkpoints, audit logging, and escalation rules.
Structured testing against task completion, reliability, and failure modes before an agent gets production responsibility.
What’s included: Test scenario design, task-completion metrics, failure-mode analysis, and pre-launch validation.
A prototype can demonstrate what AI might do. A production system needs to demonstrate that it can do it reliably, securely, repeatedly, and at the required scale.
Primotech's development process is designed around that transition.
We understand the business problem, users, existing workflows, data environment, and what success looks like.
We design the architecture, models, data flows, APIs, integrations, security, and deployment requirements for production.
We prepare data foundations through pipelines, cleaning, transformation, indexing, and knowledge bases.
Our engineers develop the models, AI applications, agents, APIs, interfaces, and supporting
We test the system against realistic business conditions, not just a clean demo dataset, covering accuracy, latency, reliability, safety, and cost.
We integrate the solution into your environment and move it to production with the infrastructure, security, and monitoring launch requires.
AI systems shift as data, users, and business needs change. We track performance, cost, drift, and outcomes, then optimize as requirements evolve.
Whether you're scaling AI across an enterprise, launching your first AI product, or need an engineering partner behind your agency, Primotech adapts its team and delivery model to your requirements.
Integrate AI into existing systems while working within enterprise security, compliance, infrastructure, and procurement requirements.
Move from concept to MVP and production without the cost and complexity of building a complete AI engineering organization internally.
Use Primotech as your white-label AI engineering arm. Keep your client relationship while we work behind your brand.
Different AI projects need different delivery models.
Best for well-defined projects with a clear scope, milestones, deliverables, and timeline.
Best for organizations building AI capabilities over a longer period and wanting direct access to an extended engineering team.
Best for projects where requirements, scope, or technical direction may evolve during development.
Ongoing AI development, maintenance, and engineering support delivered behind your brand and according to agreed SLAs.
Combine fixed-scope delivery, dedicated capacity, and ongoing support based on the needs of the project.
We build production-ready AI systems engineered for scale, security, and seamless integration with your existing technical infrastructure.
We design and build for real operating conditions, not just impressive demos. Success is evaluated against business and technical requirements before launch.
AI rarely operates alone. Our teams combine AI development with application engineering, APIs, databases, and cloud infrastructure.
We design infrastructure around expected usage, performance, reliability, security, and future growth.
Data quality, bias, explainability, access controls, and auditability are built in from architecture, not bolted on before launch.
We integrate AI with the systems you already depend on, including CRMs, ERPs, data platforms, and APIs.
Deployment is the start, not the finish. We support model updates, monitoring, and performance improvements as requirements evolve.
AI is reshaping how every industry runs, streamlining customer interactions and back-office operations alike. Primotech's AI Agent Development work spans:
Agents that investigate fraud alerts, process loan applications, and monitor compliance exceptions.
Real testing challenges. Smarter QA strategies. Measurable improvements.
We build long-term partnerships rooted in technical excellence, transparent communication, and unyielding reliability. Discover the foundation of our engineering approach.
Communicate directly with the engineers and specialists working on your project.
Your data is handled according to defined security and access requirements.
Scale your engineering capacity based on project requirements.
Your project deliverables and intellectual property remain governed by your agreed engagement terms.
Work progresses through iterative development cycles with regular reviews and feedback.
Clear milestones, progress reporting, and visibility into delivery.
Testing and QA are incorporated throughout development rather than left until the final stage.
Continue with monitoring, optimization, maintenance, model updates, and engineering support after deployment.
Dedicated engineers experienced in agent architecture, multi-agent orchestration, MCP and A2A protocols, and production deployment of autonomous systems.
Engineers experienced in LLM applications, RAG, vector databases, model integration, and scalable cloud deployment.
Full-stack engineers who build the application and infrastructure around your AI systems, including APIs, cloud infrastructure, and post-launch support.
AI systems often handle sensitive business, customer, financial, or operational data.
Primotech incorporates security, privacy, governance, and compliance requirements throughout architecture and development.
Depending on the project and industry, our work can align with relevant standards and frameworks including:
A chatbot responds to messages. An AI agent plans a sequence of steps, uses tools and APIs, and completes a task with a defined goal, sometimes without a human prompting each step.
Model Context Protocol standardizes how an agent connects to tools, data sources, and other agents. It reduces custom integration work and makes multi-agent systems easier to build and maintain.
Yes. We connect agents to your APIs, CRMs, databases, and internal tools with defined permissions, so they can complete tasks like updating records, sending notifications, or triggering workflows.
Through scoped permissions, human-in-the-loop approval on higher-risk actions, audit logging, and evaluation against realistic task scenarios before production rollout.
When a workflow has distinct stages or specialized skills that are better handled separately, such as research, drafting, and review. Multi-agent design adds coordination overhead, so we recommend it only when a single agent cannot handle the scope reliably.
A single-agent system for a well-defined task can often move from discovery to production in a matter of weeks. Multi-agent systems with several integrations typically take longer.
Yes. We monitor task completion rates, failure patterns, and system performance, and continue tuning the agent as your workflows and data change.
Yes. Most agent projects work within your existing CRM, ERP, or internal tools rather than replacing them, connecting through APIs and defined permissions.
Tell us about your AI project, integration needs, or white-label development requirements.