Manishanker Talusani

Manishanker Talusani

ABOUT ME
Founder, TryNewAI | AI-native engineering for AI-native startups & pharma
Founder, TryNewAI | AI-native engineering for AI-native startups & pharma

I'm the founder of TryNewAI, an AI-native engineering firm helping AI-native startups and pharma R&D teams ship production AI through embedded senior engineers.

Before TryNewAI, I spent six years as a senior software engineer at IPsoft, Justdial, and InMobi, building production systems across enterprise AI, search, and ad-tech. Those years taught me what most AI projects miss: getting something to work in a notebook is a different problem from making it work reliably in production, at scale, on dirty real-world data.

I founded TryNewAI in 2020 to focus on exactly that gap. Not staff augmentation. Not throw-it-over-the-wall projects. Instead, embedded engineering: senior engineers placed inside client teams, picking the highest-value AI workflows alongside leadership, and shipping them to production end-to-end.

Five years in, the model has held up:
→ ForwardEdgeAI - what began as a 3-month contract is now a 5-year continuous engagement
→ Pharma & life sciences - production AI and data engineering with Johnson & Johnson, Charles River Labs, and Haleon
→ Enterprise - engineering work with Cisco and AusNet
→ AI-native startups — including Ox.work (San Francisco)

Where I personally go deep:

  • Taking AI systems from prototype to production - eval harnesses, observability, reliability engineering
  • Data engineering for AI - pipelines, foundations, AI-ready data architectures
  • Regulated environments - pharma R&D, GxP contexts where "usually works" isn't acceptable
  • Embedded leadership - working as a fractional senior engineer or tech lead inside client teams

Who I'm best for:

-> A CTO at an AI-native startup whose AI features are stuck between prototype and production. A pharma R&D leader trying to operationalize AI inside regulated workflows
->A founder who'd rather have one senior engineer in the trenches than a five-person dev shop behind a project wall.

Hyderabad-based, working globally. DMs open — happy to talk shop even if it doesn't lead to an engagement.

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Joined February 2020
EXPERTISE
4 years experience | 1 endorsement
- Built a Intent classification system using CNN, Spacy, NLTK, Gensim to classify a given text into a specific category - Have lot of ex...
- Built a Intent classification system using CNN, Spacy, NLTK, Gensim to classify a given text into a specific category - Have lot of experience in Scraping using Beautifulsoup, Scrapy, Goose - Built a chatbot using Google Dialogflow - Built an Image classification system using Flask, Tensorflow, Transfer learning - Taught 300 students online and in classroom from basics to advanced concepts
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6 years experience
3 years experience
SOCIAL PRESENCE
GitHub
cnn_text_classification
Build a model which automatically classifies an article under Finance, Law, Fashion and Lifestyle, using the data from leading magazines for training the model.
Python
10
14
statistics_ML_jan_2020
This repo holds all code examples shared in Statistics and ML class in Jan 2020 batch
Jupyter Notebook
1
0
EMPLOYMENTS
Founder
Try New AI
2020-09-01-Present
AI-native engineering firm that gets your AI from prototype to production. Proven across pharma (J&J, CRL) and AI-native startups (Forwar...
AI-native engineering firm that gets your AI from prototype to production. Proven across pharma (J&J, CRL) and AI-native startups (ForwardEdgeAI, 5 years).
AI
LLM
Agentic frameworks
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AI
LLM
Agentic frameworks
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Dataengineering Lead
Charles River Labs
2020-12-01-2021-06-01
-Built notebooks in Azure Databricks to migrate Master Data Management customer data from Oracle to Azure Data Lake storage -Built cleans...
-Built notebooks in Azure Databricks to migrate Master Data Management customer data from Oracle to Azure Data Lake storage -Built cleansing and cleaning rules to support various business needs to enrich MDM data -Document and build pipeline in Azure Datafactory to reuse data pipelines for every data refresh -Optimize Pyspark code leveraging Databricks cluster and Spark internals to migrate data quicker
Oracle
Azure
Apache Spark
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Oracle
Azure
Apache Spark
Databricks
Azure data factory v2
Adls v2
Reltio
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Data engineer
Ausnet Services
2020-10-01-2021-03-01
-Built data pipelines in Python, Pyspark, Azure Datafactory V2, Data Vault 2.0 for ingesting data from Energy source companies like Polic...
-Built data pipelines in Python, Pyspark, Azure Datafactory V2, Data Vault 2.0 for ingesting data from Energy source companies like PolicyNet, CIS with combined data size of 20GB per day -Built data pipelines in Azure datafactory V2 to migrate data from source to destination following the bronze, silver and gold data warehousing concpet -Wrote databricks notebooks to implement Data vault data warehousing concepts to create Hub, Link and satellite. Datavault 2.0 is used to generate daily reports to the stakeholders to asses the energy consumption across Victoria region in Australia -Efficiently use Delta Lake concepts for time capsuling the data in Azure Datalake storage -Setup and co-ordinate complete Test2 infrastructure in Azure
Python
Azure
Databricks
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Python
Azure
Databricks
Adls
Databricks delta lake
Datavault 2.0
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PROJECTS
Teaching - Introduction to Python, Statistics, Machine LearningView Project
Learnbay
2019
Teach students with no prior knowledge of ml. Course structure can be viewed here : https://drive.google.com/file/d/1QMbaMyB1O8BAusq6Zc...
Teach students with no prior knowledge of ml. Course structure can be viewed here : https://drive.google.com/file/d/1QMbaMyB1O8BAusq6ZcHoZi60fYz_8wm5/view Pandas, Numpy, Matplotlib, Introduction to statistics - Mean, median, mode, variance, Standard deviation, Box plot, Histogram, Bar graph, Normal distribution, Hypothesis testing, T-test, Anova, Ancova Linear regression, Logistic regression, Decision tree, Random forest, Naive bayes theorm, SVM, Neural networks. NLP - word2vec, tokenization, Sentence classification
Python
NumPy
Pandas
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Python
NumPy
Pandas
Machine Learning
Neural Networks
Deep Learning
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Dialogflow chatbot for FrontM
FrontM
2019
FrontM platform connects people, machines, processes and partner ecosystems to create seamless mobile experiences and services, on-ground...
FrontM platform connects people, machines, processes and partner ecosystems to create seamless mobile experiences and services, on-ground, in-flight, at-sea or anywhere remote. I have designed a FAQ chatbot using Dialogflow for facilitating easy QA for customers
Google Cloud Platform
Dialogflow
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Google Cloud Platform
Dialogflow
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