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End-to-end Framework for Business Process Automation

The Need

Labor Intensive

Human intervention for ticket/incident resolution leads to higher cycle time and affects customer satisfaction.

Highly Repetitive Events

High level of incident repetition in operations.

High Cost of Operations

Amidst continuous budget cuts and pressure to improve performance, keeping service processes effective and under cost control is a challenge. The labor intensive nature of operations also results in higher cost. Pressure to continuously improve performance also results in human resource issues.

Prone to Human Error

Due to the nature of repetition coupled with high volume, business operations are usually prone to human error, leading to increased resolution time and lack of efficiency.

How does TACTiX Work?

Incident Origin

Incident originates and gets logged in the Ticketing system

Incident data is in turn fed into the TACTiX system simultaneously

Categorization

TACTiX triggers its AI component and performs the following:

Automatically categorizes incidents based on NLP algorithms and machine learning

Crawls through all knowledge repositories available

Arrives at exact resolution match or recommendation based on learning history and past system feedbacks

Recommendation

Support personnel is presented with top-matching recommendations and automation possibility along with related categories, root cause, and SOP

Resolution, Feedback Capture, and Automation

Post resolution, support personnel can schedule automated resolutions for similar incidents in the future and define the threshold for automation trigger depending on incident criticality

In case of automated resolution pathways, the system seamlessly integrates with other automation orchestration tools to resolve incidents from log and capture status while providing feedback

Proactive Incident Management

By integrating TACTiX with Operational Analytics engines, automation can also be trigged proactively ahead of incident occurrence based on trigger parameters and predictive analytics

Platform Highlights

Non-intrusive and works with existing systems

Continuously learns and improves outcomes

Uses multiple feedback and knowledge systems to continuously evolve and improve

NLP, machine learning, and text analytics to enable better decision making over time

Technology agnostic, plug-and-play framework for easy integration and quick set up

The AI engine can be trained quickly with minimum effort

Why TechM BPS?

Improved operation metrics and KPIs:

Reduced mean time for overall diagnosis and repair.

Increased customer satisfaction:

Reduced SLA violations and reduced occurrence of prevalent failure types.

Lower operations cost:

AI integration with service fulfilment and ticketing systems facilitates both reactive and proactive operation management. Over time, the evolved AI engine can also replace traditional SOP tools.

Higher utilization:

Existing resources can be freed up from repetitive tasks for value added activities.

Improved agility, speed, and ability:

Businesses can deal with changing customer requirements and market dynamics quickly without suffering operational setbacks.

Why TechM BPS?

Improved operation metrics and KPIs:

Reduced mean time for overall diagnosis and repair.

Increased customer satisfaction:

Reduced SLA violations and reduced occurrence of prevalent failure types.

Lower operations cost:

AI integration with service fulfilment and ticketing systems facilitates both reactive and proactive operation management. Over time, the evolved AI engine can also replace traditional SOP tools.

Higher utilization:

Existing resources can be freed up from repetitive tasks for value added activities.

Improved agility, speed, and ability:

Businesses can deal with changing customer requirements and market dynamics quickly without suffering operational setbacks.

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