Pranav Janardhanan

AI × AUTOMOTIVE × PRESALES

See the signal before it becomes the strategy.

I build AI-powered intelligence for teams shaping the future of mobility.

See the product Meet the builder
Automotive Watchdog
Live signals● LIVE
EV
Tariffs
Software-defined vehicles

Market noise becomes useful when patterns connect.

Automotive Watchdog tracks global stories, detects emerging patterns and turns them into decision-ready intelligence. It helps presales teams understand what matters to OEMs before the opportunity is obvious.

The product

From global news to a map of what matters next.

Automotive Watchdog is my working prototype for an automotive intelligence platform. It reads the market continuously, filters repetition, uses AI to understand each story and publishes the most relevant signals in a form that consultants and presales teams can use.

LIVE PROTOTYPE

Automotive Watchdog

A daily view of EV, software-defined vehicle, supply-chain, policy and OEM signals: summarised, scored and placed on a global map.

See the product
19automotive news feeds monitored every day
AIrelevance, category, summary, score and location enrichment
250highest-value signals ranked for daily publication
0servers to patch or keep running when the pipeline is idle

A small, serverless intelligence pipeline on AWS.

The system is intentionally lean. Infrastructure is deployed with AWS SAM, data moves through managed services, and two different AI models handle high-volume enrichment and higher-reasoning trend extraction. It runs for minutes, not all day. A newer, weekly pilot pipeline turns official company documents into cited, evidence-backed business-priority profiles.

INGEST / 05:00 UTC DAILYAUTOMATED
1

EventBridge

The daily schedule wakes up the ingestion workflow.

2

Fetch Lambda

Reads RSS feeds, keeps recent stories and removes URLs already seen.

3

SQS Queue

Buffers new articles so the enrichment stage processes them reliably.

4

Enrich Lambda

Classifies, summarises, scores and geolocates stories in batches.

Bedrock · Amazon Nova Lite
5

DynamoDB

Stores enriched articles for 14 days and maintains the deduplication index.

PUBLISH / 06:00 UTC DAILYLAST 7 DAYS
6

EventBridge

A second schedule begins the publication workflow.

7

Publish Lambda

Ranks the top 250 stories and extracts cross-market trends.

Bedrock · Amazon Nova Pro
8

S3

Publishes the map and a fresh data/news.json dataset.

9

CloudFront

Serves the private S3 origin globally over HTTPS.

10

Browser

Loads the newest intelligence directly into the live map.

COMPANY PROFILES / WEEKLY · PILOTTOYOTA · VW · TATA MOTORS
11

EventBridge

A weekly schedule: official filings update quarterly at most, unlike daily news.

12

FetchDocuments Lambda

Downloads new documents from a curated per-company source list, deliberately not a page-crawler.

13

ExtractProfile Lambda

Scans for new documents; extracts priorities with page citations, then merges them into the company's profile.

Bedrock · Amazon Nova Pro
14

S3

Writes a profile.json and a timeline.json changelog per company.

15

Browser

Company Profiles page renders each priority linked to its source document and page.

Built for low-touch operations

CloudWatch alarms watch Lambda errors and queue depth. SNS sends an email only when something fails. Adding a news source means updating sources.json; adding a company document means updating company-sources.json; changing logic means rebuilding and redeploying the SAM stack.

  • AWS SAM
  • Lambda
  • SQS
  • EventBridge
  • Bedrock
  • DynamoDB
  • S3
  • CloudFront
  • CloudWatch
  • SNS

Actual operating cost

<$1

per month at current production volume, measured from real AWS billing data, with no continuously running compute.

Pranav Janardhanan
CHENNAI, INDIAAI × AUTO

I translate complex technology into decisions people can act on.

I'm Pranav Janardhanan, a Senior Manager at LTM working across automotive, enterprise technology, presales and transformation.

My career has moved from software development at TCS, to business IT and digital product delivery at Tata Motors, and into client-facing strategy and solutioning. Across that journey, the recurring problem has been the same: valuable information exists everywhere, but decision-makers need a clearer signal. Automotive Watchdog is one practical answer to that problem.

I work best where business context, technology and storytelling meet: turning industry movements into solution hypotheses, and those hypotheses into prototypes that make an idea tangible.

CurrentSenior Manager
LTM
ManagementPGDM
IIM Shillong
EngineeringB.E. Computer Science
PSG College of Technology
View my LinkedIn profile