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Your enterprise buyers are asking whether your product has AI agents built in. Not as a demo, not as a beta feature, but as a production capability that meets their security review, works within their data residency requirements, and can be configured per account. That is a different engineering problem from building an internal automation tool.
We build agents as product features: multi-tenant architecture where each customer's agent configuration is isolated, per-customer tool registries that control what the agent can do within each account, usage instrumentation that feeds your billing system, and SOC 2-compatible controls that survive your enterprise buyers' security questionnaires. Research Triangle buyers expect this to be done right.
Who this is not for: companies building internal automation tools rather than product features, teams that need a consumer-facing AI assistant rather than a B2B workflow agent, or organizations that are not yet ready to invest in proper multi-tenant architecture.
Enterprise buyers have security teams. Security teams have questionnaires. Those questionnaires ask specific questions about data isolation, access control, and audit logging. We design for the answers to those questions from day one.
Each customer's agent runs with a tenant-scoped identity that can only access that tenant's data, tools, and configuration. We implement isolation at the storage layer (separate namespaces or row-level security), the secrets layer (per-tenant credentials), and the execution layer (tenant ID propagated through every tool call). Tenant A cannot affect Tenant B's agent state.
Enterprise customers want to configure what the agent can do within their account. We build a tool registry where your product team can enable or disable tools per customer, set rate limits per tool, and provision the credentials the agent uses for that customer's integrations. Customer admins can see what tools are active; they cannot see other customers' configurations.
Agent features need billing hooks from the start, not retrofitted later. We instrument LLM token usage, tool call counts, and workflow completions as structured events with tenant ID, action type, and timestamp. Those events feed your data warehouse or billing API. We have integrated this with Stripe metering and custom usage APIs. The numbers are accurate and auditable.
Research Triangle enterprise buyers run security reviews. We document every control relevant to your agent feature: data classification, access controls, encryption standards, audit log retention, and incident response hooks. The architecture is designed so these controls are verifiable, not just asserted. Your security team gets a technical controls document before the project closes.
The Research Triangle has a high concentration of enterprise software buyers who have been through rigorous vendor security reviews. Your agent feature will be evaluated against mature criteria.
Teams in the Triangle often have SAS workflows already in place. We build agent tool definitions that can query SAS Viya APIs or read SAS-formatted outputs, so your agent can act on the analytics your customers already produce rather than requiring a separate data pipeline.
Pendo-style product analytics apply to agent features too. We instrument agent completion rates, fallback rates, tool call patterns, and session length so your product team can see what the agent is actually doing in customer accounts and where it is failing before customers report it.
Many Raleigh engineering teams run on OpenShift or have IBM enterprise contracts. We know how to deploy agents on OpenShift and how to integrate with IBM watsonx APIs when that is required by your customer's existing enterprise agreements.
Multi-tenant, running in your environment, passing your enterprise buyer's security review criteria.
Admin interface for enabling and configuring tools per customer account, with credential management.
Structured usage events wired to your billing pipeline or data warehouse from day one.
Written documentation of every security control your auditor or enterprise buyer will ask about.
Agent-specific metrics: completion rate, fallback rate, tool call distribution, and session data.
Direct engineering access for thirty days after launch, including support for security questionnaire responses.
Multi-tenant isolation is a design-time decision, not a configuration option added later. We implement tenant-scoped tool registries where each customer's agent can only call tools provisioned for their account, with credentials stored in their own secrets namespace. Agent memory and conversation history is partitioned by tenant ID at the storage layer. Tenants cannot see each other's configurations, logs, or outputs.
We instrument every tool call and LLM invocation with structured usage events that emit to your data pipeline. From there you can aggregate by tenant, by workflow, or by action type and feed the numbers into your existing billing system. We have built this on top of Stripe metering, custom usage APIs, and internal data warehouses. The instrumentation ships with the agent, not as a separate project.
Cost depends on the number of tools in the agent's registry, the complexity of per-customer configuration, and whether you need usage metering wired to billing from day one. We start with a paid discovery phase that scopes the work in detail, and quote fixed scope after discovery.
We document the agent as a sub-processor in your data flow maps, implement role-based access controls on every tool the agent can call, produce immutable logs of every agent action for your audit trail, and apply encryption at rest and in transit throughout. We write the technical controls documentation your auditor will ask for, and we walk your security team through the architecture before we start building.
More questions? Send us a message or read the full service overview.