Eranova
Map your use case
Professional & Business Services

Deploy AI Agents Across Back Office Operations

Trusted by industry leaders to scale operations without increasing manual overhead

Map your use case

81%

Average reduction in manual overhead

1M+

Fortune 500 Agentic jobs processed

Industry Applications

AI agents for client delivery operations

Application
City office building exterior

Contract validation

[01]

Scroll to explore this application

ROI[1.1]

68%
Contract review time reduced

Summary[1.2]

Parse agreements and flag non-standard terms for legal or delivery teams.

Inputs[1.3]

Client agreements and SOWs
Clause libraries and playbooks
Rate cards and pricing terms
Risk and approval thresholds

Actions[1.4]

  1. 01
    Extract key commercial terms and dates.
  2. 02
    Compare clauses to approved standards.
  3. 03
    Flag deviations and missing language.
  4. 04
    Draft redlines and approval summaries.

Outcomes[1.5]

Faster contract turnarounds
Reduced legal review bottlenecks
Consistent commercial standards
Lower risk exposure
Application
Professional services team collaborating

Delivery knowledge agents

[02]

Scroll to explore this application

ROI[2.1]

62%
Knowledge requests deflected

Summary[2.2]

Agents connected to internal knowledge bases and project archives to answer client questions.

Inputs[2.3]

Project archives and deliverables
Playbooks and templates
Knowledge base articles
Client FAQs and histories

Actions[2.4]

  1. 01
    Answer delivery questions with citations.
  2. 02
    Recommend relevant assets and templates.
  3. 03
    Summarize prior project outcomes.
  4. 04
    Escalate edge cases to specialists.

Outcomes[2.5]

Reduced time spent searching for info
Faster client response cycles
Consistent delivery guidance
Improved onboarding for new staff
Application
Knowledge base and documents

Shared inbox automation

[03]

Scroll to explore this application

ROI[3.1]

59%
Inbox triage automated

Summary[3.2]

Automate client support and project queries with routing and templated responses.

Inputs[3.3]

Client emails and support requests
Account and project context
SLA and priority rules
Response templates

Actions[3.4]

  1. 01
    Classify inbound requests by intent.
  2. 02
    Extract key details and project IDs.
  3. 03
    Route to the correct team or owner.
  4. 04
    Draft responses with context.

Outcomes[3.5]

Faster response times
Reduced manual triage effort
Clearer accountability by team
Improved client satisfaction
Application
Office workspace with documents and laptops

Engagement operations automation

[04]

Scroll to explore this application

ROI[4.1]

54%
Ops tasks automated

Summary[4.2]

Automate repetitive engagement tasks like status updates, reporting, and document prep.

Inputs[4.3]

Project plans and timelines
Timesheets and status notes
Client reporting templates
CRM and PM system data

Actions[4.4]

  1. 01
    Generate weekly status summaries.
  2. 02
    Compile metrics and deliverable progress.
  3. 03
    Update CRM/PM tools with new data.
  4. 04
    Flag risks and overdue items.

Outcomes[4.5]

Reduced admin workload
More consistent client reporting
Improved project visibility
More time for client delivery
Agentic models supported
OpenAI
Anthropic
Gemini
Llama
xAI
Governed Integrations

AI agents connected directly to your enterprise systems

[01]

Enterprise systems

ERP
TMS
CRM
Accounting
WMS
OMS
[02]

Communication

Outlook
Gmail
Teams
Slack
[03]

Data & Storage

SQL Databases
SharePoint
Data Warehouses
Google Drive
[Scoped permissions][Agent audit trails][Human in the loop][Workflows run safely at scale]
Indicators of High ROI Workflows

How to spot AI agent opportunities

Manual data entry[01]

Which processes still require significant manual data entry or re-keying between systems (ERP, TMS, WMS, CRM, spreadsheets)?

Heavy document processing[02]

Which workflows rely on large volumes of semi-structured documents (invoices, contracts, BOLs, manifests, forms)?

Varying input structure[03]

Which processes rely on inputs with high variance (PDF formats, free-form text, email attachments)?

Email inbox monitoring[04]

Which shared inboxes require constant manual monitoring, triage, and follow-up to keep up with customers, suppliers, or partners?

Repetitive manual tasks[05]

Which rule-based, repetitive tasks drive the most overtime, headcount, or SLA risk?

Highest value targets[06]

Which of these repetitive workflows would drive the most value if an AI agent could run them end-to-end?

Use these indicators to uncover workflows where AI agents can drive down manual overhead.

Become the Industry Standard.