Enterprise automation needs
intelligence, not just
execution.

Building AI agents is the easy part. Discovery, governance, reliability, and continuous improvement at enterprise scale are the hard parts. AutomationCOE exists to solve them.

TECNOPRISM'S TRACK RECORD

A decade of enterprise delivery powers every decision we make.

AutomationCOE is not a theory. It is the direct product of thousands of enterprise engagements across industries where reliability, governance, and measurable ROI are non-negotiable requirements.

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Years of enterprise AI & automation delivery

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Enterprise projects delivered globally

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Industries served across regulated sectors

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Countries with active delivery engagements

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AI & automation specialists on the team

THE PROBLEM

Where enterprise automation programs break down.

Automation programs fail at the same structural points every time, across every industry.
AutomationCOE was designed to close each of those gaps.

WITHOUT AUTOMATION COE

Manual discovery

3–6 weeks per process before a bot is scoped

Siloed teams & tooling

No reuse; the same automation built multiple times

No governance framework

Quality and compliance vary by project and analyst

Duplicate automations

Budget wasted on redundant, fragmented delivery

Runtime failures

Detected only after business impact has occurred

No operational visibility

No way to know if the estate is healthy or failing

Automation CoE Logo

AutomationCOE

WITH AUTOMATION COE

Standardised discovery

ARIA converts videos to PDDs in minutes, not weeks

Enterprise governance

One intake model, one delivery standard, enterprise-wide

Reusable component library

Build once, deploy many times across the estate

Continuous intelligence

AURA monitors every automation in real time

Predictive operations

Failures prevented before they reach the business

Real-time estate visibility

Every bot, every dependency, on one unified dashboard

ARIA · Process Discovery
● Analyzing
Video → Step extraction
PDD generation
Test case creation
Feasibility scoring
DISCOVERY AGENT

ARIA

The AI-powered discovery intelligence that transforms business processes into structured automation requirements automatically.

ARIA watches process videos, understands what is happening, and generates the complete automation package PDDs, test cases, feasibility reports, and PII-safe documentation in a fraction of the time that manual discovery requires.

  • Process video analysis and step extraction
  • Automated PDD generation - 92% faster than manual
  • Test case and feasibility report creation
  • PII identification and redaction built in
Explore ARIA in depth
ASSURANCE AGENT

AURA

The runtime intelligence layer that ensures automation reliability before business impact can occur.

AURA monitors every automation in production, maps dependencies, predicts failures, and resolves incidents faster through automated root cause analysis. When the estate grows, AURA ensures reliability scales with it.

  • Real-time monitoring across the full automation estate
  • Dependency mapping - know what breaks when one thing fails
  • Predictive alerting - incidents resolved before business impact
  • Automated root cause analysis and resolution guidance
Explore AURA in depth
AURA · Operations
99.5% SLA
SAP-PROD auth timeout · 2 bots at risk
8s

THE METHODOLOGY

The 5D1S Framework

AutomationCOE delivers every engagement through a proven six-stage operating model, five delivery dimensions and one sustaining discipline, ensuring consistent quality, governance, and outcomes from first discovery to live production.

D1 · DISCOVER

Surface automation opportunities at enterprise scale

ARIA-powered AI analysis identifies and prioritises automation candidates from process videos, interviews, and existing documentation - without manual surveys or lengthy workshops.

  • Process video analysis
  • Opportunity scoring
  • Feasibility assessment
  • PDD generation

BUSINESS OUTCOME

A qualified backlog of automation opportunities, ranked by ROI and complexity.

D2 · DOCUMENT

Establish clear, governed requirements for every automation

Each opportunity is structured into a validated Process Definition Document with test cases, exception handling, and business rules — eliminating ambiguity before development begins.

  • Requirements structuring
  • Exception mapping
  • Test case generation
  • Stakeholder sign-off

BUSINESS OUTCOME

Complete, developer-ready specifications that reduce rework by over 60%.

D3 · DEFINE

Architect automations for reliability and reusability

Automation architects design solutions using standardised patterns, reusable components, and the enterprise integration framework — ensuring every automation is built to last.

  • Solution architecture
  • Component reuse
  • Integration design
  • Security review

BUSINESS OUTCOME

Modular automation designs that reduce build time and increase long-term reliability.

D4 · DEVELOP

Build, test, and validate with enterprise-grade rigour

Development follows the CoE delivery standard — unit tests, UAT frameworks, and automated regression suites — ensuring quality before any automation reaches production.

  • Bot development
  • Unit testing
  • UAT execution
  • Performance validation

BUSINESS OUTCOME

Production-grade automations with full test evidence and documented sign-off.

D5 · DEPLOY

Release with governance, monitoring, and dependency clarity

AURA establishes operational baselines and dependency maps before go-live. Every deployment is monitored from day one, with alerting calibrated to the specific risk profile of each automation.

  • Dependency mapping
  • AURA onboarding
  • Incident playbooks
  • Go-live approval

BUSINESS OUTCOME

Automations in production with full operational visibility from the first minute.

1S · SUPPORT

Continuous improvement through operational intelligence

AURA monitors every automation in production — predicting failures, resolving incidents, and surfacing optimisation opportunities. New discovery cycles begin automatically as business processes evolve.

  • Continuous monitoring
  • Predictive alerts
  • Root cause analysis
  • Optimisation surfacing

BUSINESS OUTCOME

A self-improving automation estate that becomes more reliable over time.

AUTOMATION MATURITY

Six stages from reactive to autonomous.

Every enterprise automation programme occupies one of these six stages. AutomationCOE is the operating model that moves organisations from stage 1 to stage 6 — systematically and sustainably.

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Reactive

Automation is deployed project by project with no standards, governance, or reuse across the organisation.

Primary capability: Individual bot delivery

2

Organised

A basic RPA programme exists with some delivery standards, but governance and operational visibility remain limited.

Primary capability: Consistent RPA delivery

3

Governed

COE

An AutomationCOE is established. Intake, delivery, and documentation follow a standardised operating model across the enterprise.

Primary capability: COE-driven delivery

4

AI-Augmented

COE

ARIA accelerates discovery and documentation. AI is embedded in the intake and delivery process, compressing timelines significantly.

Primary capability: Intelligent discovery

5

Predictive

COE

AURA monitors and predicts failures before they impact the business. Incident response shifts from reactive to proactive.

Primary capability: Proactive operations

6

Autonomous

COE

The automation estate continuously discovers, deploys, monitors, and improves itself - with AI orchestrating the full lifecycle end to end.

Primary capability: Enterprise intelligence

MEASURED IMPACT

The difference isn't theoretical.

Outcomes measured across active enterprise deployments, not analyst benchmarks.

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Faster process discovery

Measured time from process identification to automation-ready PDD, compared to manual discovery methods.

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SLA across managed automation estates

Uptime commitment across production bot estates under AURA operational monitoring, across all managed enterprise clients.

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Bots managed globally

Active automations across 60+ enterprise clients in 12 industries.

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Lifecycle cost reduction

Reduction in total automation program cost when discovery, documentation, and runtime assurance are unified under AutomationCOE.

FAQ

Common questions about AutomationCOE.

Not finding your answer? Email us directly.

Enterprise automation requires more than bot development. AutomationCOE addresses the broader lifecycle of automation, including process discovery, governance, reusable components, deployment, runtime monitoring, predictive operations, and continuous improvement. This helps organizations reduce fragmented delivery, duplicate automations, runtime failures, and limited visibility across their automation estate.
AutomationCOE uses ARIA, its AI-powered discovery intelligence, to analyze process videos and extract workflow steps automatically. ARIA can generate Process Definition Documents (PDDs), test cases, feasibility reports, and PII-safe documentation, significantly reducing the time required for manual process discovery.
The 5D1S framework is AutomationCOE's six-stage operating model covering Discover, Document, Define, Develop, Deploy and Support. It provides a standardized approach to automation delivery, from identifying opportunities and defining requirements through development, production deployment, monitoring, and continuous optimization.
AutomationCOE uses AURA as a runtime intelligence layer to monitor automations in production, map dependencies, predict potential failures, and support automated root-cause analysis. This enables organizations to identify and address automation issues before they create significant business impact.
AutomationCOE provides standardized intake, delivery, documentation, security, testing, monitoring, and governance practices across the enterprise. Its reusable component approach and unified operational visibility help organizations avoid duplicate automations while maintaining consistent standards across teams and business units.
AutomationCOE defines six automation maturity stages: Reactive, Organised, Governed, AI-Augmented, Predictive, and Autonomous. Organizations can use this maturity model to understand their current capabilities and progressively introduce standardized governance, AI-powered discovery, predictive monitoring, and eventually autonomous automation lifecycle management.