Custom AI Agents Built for Your Business

Purpose-built AI agents that handle customer inquiries, analyze data, orchestrate workflows, and more.

Getting started

We begin with stakeholder interviews to understand your workflows, pain points, and desired agent capabilities. We then define the agent's persona, audit your knowledge base, and assess risks before designing the architecture.

What's included

Stakeholder interviews and use case definition

Agent persona, tone, and behavioral boundary design

Knowledge base audit and RAG pipeline development

Prompt engineering with guardrails and safety layers

Red team testing and adversarial validation

30-day hypercare with conversation analytics and optimization

How we deliver

A structured, phase-gated process. Every phase includes formal sign-off before proceeding to the next.

01

Requirements & Use Case Definition

1–2 weeks

We interview your stakeholders, define each agent's purpose and success criteria, establish its personality, and audit the knowledge it will need access to.

What we do

  • Stakeholder interviews to understand workflows and pain points
  • Use case documentation with scope, inputs, outputs, and success criteria
  • Persona and tone definition with brand alignment
  • Knowledge base audit of existing docs, FAQs, and data sources
  • Risk and ethics assessment for failure modes and guardrails

What you get

  • Agent use case specification
  • Agent persona profile and tone guidelines
  • Knowledge base inventory with access requirements
  • Risk and ethics report with mitigation strategies
02

Architecture & Prompt Design

1–2 weeks

We design the agent framework — model selection, tool integrations, prompt engineering, guardrails, and conversation flow mapping.

What we do

  • Architecture design with model selection and memory strategy
  • Prompt engineering with chain-of-thought templates
  • Tool and API design with function-calling schemas
  • Guardrail framework with content filtering and escalation triggers
  • Conversation flow mapping with edge cases and handoff scenarios

What you get

  • Agent architecture document with component specs
  • Versioned prompt library with testing notes
  • Tool and API specification
  • Guardrail policy document and escalation matrix
  • Conversation flow diagrams with branching logic
03

Development & Training

2–4 weeks

We build the core agent, ingest your knowledge base, connect to your systems, create evaluation benchmarks, and iteratively tune prompts.

What we do

  • Core agent build with model integration and state management
  • Knowledge ingestion via RAG pipeline or fine-tuning preparation
  • Integration development with your CRM, helpdesk, and databases
  • Automated evaluation suite for accuracy, relevance, and safety
  • Iterative prompt tuning based on eval results

What you get

  • Functional AI agent in staging environment
  • Indexed and retrievable knowledge base
  • Working API integrations with error handling
  • Evaluation report with benchmark scores
  • Prompt version history with performance deltas
04

Testing, Validation & Launch

2–3 weeks

Adversarial red team testing, stakeholder beta, performance benchmarking, production deployment, and team training.

What we do

  • Red team testing for prompt injection and abuse scenarios
  • Stakeholder beta with structured feedback collection
  • Performance benchmarking (latency, accuracy, cost)
  • Go-live deployment with monitoring and rollback capability
  • Team training on agent management and escalation procedures

What you get

  • Red team test report with remediations applied
  • Beta feedback summary with adjustments made
  • Performance baseline report (latency, accuracy, cost)
  • Deployment runbook with incident response
  • Training materials and admin documentation
05

Monitoring, Learning & Evolution

30 days + ongoing

30 days of active monitoring, conversation analytics, knowledge base updates, and a path to ongoing managed service.

What we do

  • 30-day hypercare with rapid bug fixes and behavioral adjustments
  • Conversation analytics for quality and improvement opportunities
  • Knowledge base updates as new information becomes available
  • Model and prompt upgrades as better models release
  • Transition to managed service or retainer

What you get

  • Monthly performance report with quality scores
  • Continuous improvement log with impact measurements
  • Quarterly strategy review for agent expansion
  • Managed service agreement with SLA and pricing

Frequently Asked Questions

A chatbot typically follows pre-scripted conversation flows. An AI agent is powered by large language models and can understand context, reason about problems, access tools and data, and take actions autonomously. Our agents are far more capable than traditional chatbots.

Yes. We build agents that connect to your CRM, databases, email, helpdesk, and other tools via APIs. If your software has an API, we can integrate it. We document all connections during the architecture phase.

We use retrieval-augmented generation (RAG) to ground responses in your actual data, plus guardrails including content filtering, hallucination detection, and human-in-the-loop gates. We also run adversarial red team testing before launch.

Pricing varies based on complexity, integrations, and scope. We provide a detailed Statement of Work with fixed or estimated pricing after the discovery phase. Every engagement includes a clear scope, timeline, and milestone-based delivery.

Typically 6-10 weeks end-to-end: 1-2 weeks for requirements, 1-2 weeks for architecture, 2-4 weeks for development, and 2-3 weeks for testing and launch, followed by 30 days of hypercare.

See It in Action

Real-world examples of how businesses use this service to drive results.

View all use cases
Healthcare

AI Receptionist for Dental Clinics: Stop Losing Patients to Missed Calls

Dental clinics lose thousands in revenue every month from missed calls. An AI receptionist answers every call, books appointments, and sends reminders — without adding to your payroll.

Read use case
Legal

AI Contract Review for Small Law Firms: Cut Review Time by 60% Without Cutting Corners

Solo practitioners and small law firms are using AI to slash contract review time by 60 percent. With 53 percent of small firms already using generative AI, the question is not whether to adopt — it is how fast.

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Real Estate

AI Lead Qualification for Real Estate: Turn Every Inquiry Into a Qualified Prospect

Real estate agents drown in unqualified leads while hot prospects slip away. AI agents that work around the clock are boosting lead volume by 300 percent and increasing conversion rates by 30 to 40 percent.

Read use case
Real Estate

AI Tenant Communication and Maintenance for Property Managers: 24/7 Service Without 24/7 Staff

Conversational AI handles tenant communications around the clock — maintenance requests, rent inquiries, lease questions — and dispatches contractors automatically. Property managers report a 30 percent reduction in on-property labor hours.

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Restaurants & Hospitality

AI Voice Ordering for Restaurants: Every Phone Call Answered Without Staffing the Phone

With 80% annual turnover making phone staffing a nightmare, restaurant voice AI processes orders, integrates with your POS, and handles upselling — so every call becomes revenue instead of a missed opportunity.

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Healthcare

AI Remote Patient Monitoring for Allied Health: Better Outcomes Between Visits

Wearable biosensors paired with AI track exercise adherence and recovery between visits for physio, chiro, and rehab clinics — improving patient retention by 15 to 25 percent and delivering measurably better outcomes.

Read use case

Ready to Get Started with Custom AI Agents?

Book a free consultation to discuss your needs and see how we can help.