AI Agents

AIGard builds AI agents that take actions across your tools, such as looking up records, filing tickets or running workflows, with permissions and guardrails. We design them to be auditable and safe to run in production.

The work typically covers:

• Agent and tool design
• Integration with internal systems and APIs
• Permissions, approvals and human-in-the-loop steps
• Evaluation and red-teaming
• Logging and audit trails
• Monitoring and continuous improvement

AI Agents is usually the right investment in one or more of these situations:

• Multi-step work is repetitive but needs judgment
• Staff switch between many tools to finish one task
• You want an assistant that acts, not just answers
• Existing automation breaks on exceptions

On a 30-minute scoping call we confirm whether it fits your case and recommend a team shape and first milestones.

AIGard controls AI agent behavior by limiting what each agent can access, requiring approval for sensitive actions, testing against adversarial cases and logging every step.

Permissions, approvals and human-in-the-loop steps are designed alongside the agent's tools, not added afterward. Evaluation and red-teaming take place before release, and logging and audit trails make each action reviewable once the agent is running in production.

A chatbot answers questions. An AI agent can also take actions in other systems to complete a task.

Examples of agent actions include looking up records, filing tickets or running workflows across your tools. Because an agent acts as well as answers, AIGard designs it with permissions, guardrails and audit trails so that it is auditable and safe to run in production.

By treating the model as one part of a system. Production work covers data pipelines, evaluation, deployment, monitoring and retraining as well as the model itself.

We agree the success metric first, assess whether your data supports the use case, and build the surrounding engineering so the system keeps performing after launch.

Privacy and security controls for each AI use case are defined up front, and engineers work inside your environment under least-privilege access.

We agree which AI tools and models may access your code and data, including retention and training settings, with human approval for sensitive actions.

For AI Agents, AIGard engineers typically work with Anthropic, OpenAI, LangChain, LlamaIndex, Python and Kubernetes.

The stack is selected to fit the systems you already run, and engineers are matched to it before they join.

AI Agents is available through any of AIGard’s three engagement models: staff augmentation, where engineers join your team; a dedicated team that runs the workstream; or software outsourcing, where AIGard delivers a defined project.

The choice depends on how much of the delivery you want to manage, and it can change later under the same agreement.

Engineers typically start within two to four weeks of the scoping call. The exact date depends on the roles, seniority and number of people required.

We confirm a realistic start date in writing before you commit, and you meet the proposed engineers before work begins.

AIGard engineers typically cost 30–50% less than the fully loaded cost of a comparable US-based hire, with no recruiting fees, benefits overhead or insurance costs on your side.

The figure for a specific engagement depends on the model, the roles, the seniority mix and the size of the team. We issue a written proposal after the scoping call, so the commercial terms are agreed before any work starts.

NDAs are signed before any access is given, and engineers work inside your environment under least-privilege access, with permissions limited to their responsibilities.

Access is reviewed as roles change and removed when work ends. Our practices align with ISO 27001, SOC 2, GDPR and HIPAA, with PII masking, encryption and audit logging built into data work. We review your access policies, data-handling needs and vendor requirements during scoping.

You do. Intellectual property assignment is written into every contract, in every engagement model.

That covers source code, designs, documentation, data, models and prompts produced for you. Third-party components and their licenses are identified, so ownership is clear at handover.