KeenSight Analytics

Core Service

Custom AI Development

Purpose-built AI systems engineered around your workflows, data, users, integrations, controls, and operating requirements. This is the core of KeenSight's delivery model.

Starting investment: $75,000+ for production implementations

When the workflow matters too much for an off-the-shelf product

Custom AI development is the right fit when your process spans multiple systems, depends on proprietary data or business logic, requires differentiated user experience, or needs explicit security, governance, and human-review controls. We design the system around the way your organization actually operates rather than asking your organization to adapt to a generic AI product.

Good fit when

  • The workflow is differentiated, complex, or strategically important.
  • The solution must connect to existing SaaS, APIs, databases, documents, or internal systems.
  • You need production-grade permissions, evaluation, auditability, exception handling, or human review.
  • A prototype exists, but it needs to become a reliable production system.
  • You want to own a tailored capability rather than license another generic platform.

What this engagement creates

Outcomes built around your operating environment

Bespoke AI applications

Internal tools and customer-facing applications designed around a specific operating problem and user experience.

Agentic workflows

Single-agent or multi-agent systems that reason, retrieve, act, coordinate, and escalate within defined business boundaries.

Enterprise integrations

Connections to the systems your teams already use, including APIs, data stores, document repositories, SaaS platforms, and internal services.

Governed automation

Permissions, human review, exception paths, logging, evaluation, and control mechanisms designed into the workflow.

Production architecture

Software architecture, model selection, data flows, observability, deployment, and operational design appropriate to the use case.

Measured outcomes

Evaluation criteria tied to the workflow: quality, throughput, accuracy, cycle time, cost, adoption, or other business measures.

Typical deliverables

What you can expect

  • Solution architecture and implementation plan
  • Production application, workflow, or agent system
  • Required data and enterprise integrations
  • Evaluation framework and acceptance criteria
  • Human-review, escalation, and exception handling
  • Security, permissions, logging, and operational controls
  • Deployment, documentation, and handoff
  • Optional managed support and ongoing engineering

How we work

1

Frame the operating problem

Define the users, workflow, business objective, systems involved, constraints, and success measures.

2

Design the solution

Translate the operating problem into architecture, data flows, model boundaries, integrations, controls, and delivery scope.

3

Build and evaluate

Develop iteratively against representative workflows, data, edge cases, and acceptance criteria.

4

Deploy and operationalize

Integrate the system into production with monitoring, permissions, governance, documentation, and team handoff.

Start with the business problem

If the problem is well defined, we can scope a direct implementation. If important workflow or architecture questions remain, we may recommend a Blueprint or bounded Production Pilot first.

Schedule a consultation