Turn your highest-value AI use case into a working, measurable pilot.
Athena designs, builds, and tests AI agents, copilots, and workflow automations on your real processes — with structured governance, performance benchmarks, and a clear scale or stop recommendation at the end.
The step after strategy.
The AI Transformation Blueprint identifies which use cases to prioritise and why. The AI Agent & Automation Studio takes the top 1–3 use cases from that roadmap and converts them into working pilots — connected to your real data, tested against your real workflows, and measured against agreed KPIs.
Five formats — one structured approach.
Knowledge Assistant
Answers employee or customer questions from internal documents, SOPs, and knowledge bases — with source attribution and role-based access.
Copilot
Supports human decision-making by surfacing customer history, generating proposal drafts, flagging risks, and preparing recommendation packages.
Autonomous Agent
Handles a defined end-to-end task — classifying, routing, escalating, and preparing actions — with human approval at critical decision points.
Workflow Automation
Replaces repetitive manual steps in a process with AI-driven automation — reducing handling time, error rates, and operational overhead.
Intelligence Dashboard
Makes operational data queryable in natural language — providing executives, managers, and analysts with instant, accurate answers without requiring BI expertise.
What we typically build.
Customer Support Agent
Classifies, prioritises, and routes support requests — with response suggestions and sentiment analysis.
Sales Copilot
Surfaces customer history, generates quote proposals, and prepares objection-handling playbooks before each call.
Knowledge Assistant
Answers employee questions from internal documents and SOPs — with cited sources and role-based access.
Product Advisor Agent
Conducts needs assessments in natural language, compares options, and delivers personalised product recommendations.
Operations Agent
Analyses operational records, flags anomalies, and routes issues with context to the right teams.
Executive AI Dashboard
Makes business data queryable in plain language — delivering instant management insight without BI dependency.
How an agent pilot actually works.
AI Agent Workflow
Customer Support AgentReceive
Input
Inbound request received and parsed from customer channel
Analyse
Context
Intent classified, customer history retrieved, sentiment assessed
Decide
Action
Response strategy selected based on intent, policy, and priority rules
Act
Execute
Response drafted, systems updated, escalation triggered if required
Report
Outcome
Interaction logged, performance metrics recorded, handoff documented
- 1
Receive
Input
Inbound request received and parsed from customer channel
- 2
Analyse
Context
Intent classified, customer history retrieved, sentiment assessed
- 3
Decide
Action
Response strategy selected based on intent, policy, and priority rules
- 4
Act
Execute
Response drafted, systems updated, escalation triggered if required
- 5
Report
Outcome
Interaction logged, performance metrics recorded, handoff documented
Six phases from scope to scale decision.
Scope
Clarify use-case boundaries, target users, data sources, and success metrics.
Pilot Scope Document
Data
Identify, clean, and structure the data layer the agent will operate on.
Pilot Dataset & Knowledge Base
Design
Define agent behaviour, human approval points, escalation logic, and response rules.
Agent Behaviour Specification
Build
Develop the working prototype — interface, workflow, integrations, and logging.
Working Pilot v0.1
Test
Run test scenarios, edge cases, hallucination checks, and user acceptance testing.
QA Report & Improvement Backlog
Pilot & Measure
Run with selected real users, measure KPIs, collect feedback, produce scale recommendation.
Pilot Performance Report
A complete pilot package — not just a demo.
- Pilot Scope Document — use case, users, data sources, success criteria
- Agent Behaviour Specification — what the agent does, what it cannot do, human approval rules
- Data & Knowledge Base Pack — cleaned, structured, ready for production
- Working Pilot — web interface, chatbot, copilot panel, or workflow automation
- Test Scenario Pack — happy path, edge cases, hallucination and accuracy tests
- Pilot Performance Report — usage, accuracy, time savings, and business impact
- Scale Recommendation — scale, iterate, or reprioritise with evidence
Three pilot formats.
3–4 weeks
Limited-scope knowledge assistant or simple assistant pilot. Single use case, document-based, basic interface.
5–6 weeks
Athena's core format. Real data, RAG knowledge base, workflow design, live user pilot, KPI measurement, and scale recommendation.
7–8 weeks
Integrated pilot with system connections, human approval workflows, role-based access, and a scale architecture document.
Governance built in from day one.
Every pilot defines what the agent can and cannot do, where human approval is required, how data access is scoped, and how outputs are logged. Governance is not a phase — it is a design constraint applied from scope to production.
Let's identify your highest-value pilot starting point.
A Discovery Session maps your processes, data, and AI readiness — and returns a clear use-case recommendation for your first pilot.