Kritika Tyagi

- Implemented Enterprise Agentic AI as a Product Manager/Subject Matter Expert for GTM Sales Org, using Claude LLM to extract data from pdf files improving the search retrieval time by >80% - Implemented Enterprise Agentic AI for Account Planning reducing the time taken to create account plans by 90% - Created efficient Prompts to get accurate results via testing and approval of the results - Continuous effort to maintain clean data in Enterprise Business Systems to be used as a source of truth to train the LLM - Implementing Sales Planning Module from SFDC to reduce manual planning effort in spreadsheets over a period of 3months. The module will automate sales processes and also eliminate 2 days of SFDC downtime for deployment

- Implemented Data Migration project for an architectural overhaul of cross functional business systems to drive automation from Lead to Cash with off shore consultants and internal Enterprise Architecture teams to reduce admin tasks by 70% - Implemented Partner Relationship Management platform for Global Partner Alliance team on Force.com for easy interaction and collaboration with partners to drive higher sales revenue improving process efficiency by 80% - Continuous improvement to existing CRM platform to drive better data driven decisions improving the overall platform health and reducing manual approvals by 60%

- Optimized SFDC sales opportunity UI by reducing user touch points by 20% and automating processes from accounts and contacts. - Improved quoting experience across sales and finance organizations by reducing redundancies in systems and saving users 30% of their total quoting time. - Improved users Contact Management experience along with marketing by automating contact relationship status with multiple accounts saving Account Managers 5hrs per month. - Improved Prospecting for ISRs by enabling them the ability to manage their own campaigns thereby reducing approximately 2 days of waiting time per Campaign

- Spearhead the sales realignment project every year in January while coordinating with all different business units like ServiceNow, Data Warehouse, Callidus, Eloqua, Aprimo, Seismic and PowerBI to make sure that all systems inherit the accurate sales data from Salesforce. - Implemented Salesforce Orders to ERP Integration to ensure smooth operations to book orders in ERP saving finance around a day for every order booked by eliminating manual checks in Salesforce to make sure that right order was being against the ERP number and right sales team was tagged - Implemented Salesforce to ServiceNow Integration to make sure service entitlements flow down to SNow accurately saving the Customer Services team a couple hours for every order by eliminating manual data entry in the in-house legacy system - Implemented Integration between Salesforce, In-house Data Warehouse and Callidus to make sure right sales team was eligible for compensation for every deal booked

- Implemented LinkedIn Sales Navigator, D&B integration and Finlistics for prospecting by sales team - Implemented Conga for sales teams which is used to generate financial reports through spreadsheets - Created standard pipeline and audit reports and dashboards for business and sales leadership to identify anomalies on a monthly basis

- Maintained accurate data across Salesforce, ServiceNow, Callidus and Data Warehouse - Implemented processes to maintain data quality through MDM between Salesforce, Financial Systems and PowerBI

-Implemented Salesforce CPQ Sales Process to improve the overall sales revenue by 30% from previous FY. -Implemented consistent pricing across all products to reduce the Sales Reps’ execution time by 1.5 minute per transaction. -Built a product-based transaction model to reduce redundancy in the product selection for different terms of subscription. -Built consistent data model in CPQ for accurate data and reporting analytics to further assist in data driven decision making.

-Developed a Brand Sentiment Analysis engine in Python to help FYI identify potential influencers for specific brands to expand their influencer marketing business. -Developed a complimentary search engine to help FYI find current influencers for the brand’s product launch campaigns.

-Developed a stochastic model running regression and KNN techniques to derive the optimal launch angle for a baseball batter to increase player performance metrics. -Developed the final predictive model by combining the results of machine learning algorithms and stochastic model simulations and visualised the results on Tableau.

•Recorded and published online lectures on ASU’s Blackboard website.

-Developed an ensemble model of Neural Networks, Random Forest, Boosted Decision Tree and Support Vector Machine for a highly imbalanced dataset in Azure ML to predict fraudulent cases in order to issue credit cards to the customers.

•Optimized the design of the turbine by assembling and summarizing the “Welding”, “Casting” and “Machining” drawings data and making presentations of the findings and recommendations as a member of cross functional, multinational team of 5 and resulted in $15 million cost cutting from design conceptualization to modelling. •Provided KPIs, analysed metrics using 6sigma technique in the manufacturing process as a part of team of 5 engineers that were used by the management to save additional $10 million. •Provided information to management by assembling and summarizing the “Assembly Drawings” data, preparing reports and making presentations of findings, analyses, and recommendations that were used to save additional $5 million. •Implemented the decisions made from the above findings in further R&Ds with global teams and resulted in optimized cost products of best quality. •Received “Outstanding Achievement Award” for optimization and cost reduction of the turbine efficiency. •Participated in 3-member team for Customer Review Meeting to review the final turbine design before installation on site based on exceptional performance.