Data Engineering & AI Automation · India · UAE · Europe · North America
TryData turns data chaos into automated systems that finance teams, ops teams, and customers can actually rely on: AI agents, data pipelines, and dashboards built to survive real load, not just demos.
30+
Cloud systems deployed
zero production failures
10+
Years in data engineering
FinTech, logistics, D2C
50+
Client engagements
India, USA & beyond
$180K
Saved for one FinTech client
analyst hours per year
Who we work with
Deep domain knowledge beats generalist delivery every time. Pick the one that fits.
Your analysts are buried in Excel reconciliations, regulatory exports, and audit prep. Every month. Decisions wait. Errors compound. Regulators don't.
$180K
analyst hours saved annually, verified by one FinTech client
CAC keeps climbing. Post-purchase visibility is a black box. Your marketing team is optimising spend without knowing which customers actually stick around.
3.2×
marketing ROI lift across a 6-month D2C engagement
Client results
Real results from client engagements. Details anonymised.
FinTech
Data Engineering + BI8 weeks · New York, USA
Before us
The finance team had tried two offshore vendors. Both delivered Excel-based reports that still required 3 weeks of manual validation. The CFO couldn't trust the numbers before board meetings.
The problem
Month-end close took 3 weeks in Excel across 6 disconnected source systems. Reconciliation errors reached 9%, blocking strategic decisions and causing quarterly board-pack delays.
What we built
Built an automated Airflow pipeline ingesting from 6 sources into Snowflake, with dbt transformations enforcing data contracts at every layer. Deployed a real-time financial dashboard with anomaly alerting so errors surface in hours, not weeks.
"Excellent working with Dheeraj. Deep expertise around AWS and ETL pipelines. Month-end reports now run in 2 hours, not 3 weeks."
3 wks → 2 hrs
Report generation
99.8%
Data accuracy (was 91%)
$180K / yr
Analyst hours saved
D2C E-commerce
AI Applications + Analytics10 weeks · India
Before us
The brand was running batch email blasts to their full list. They had Klaviyo but no behavioural segmentation. CAC had risen 34% over 12 months while repeat purchase rate fell.
The problem
No post-purchase visibility. Rising CAC, high churn, unoptimised ad spend, and no way to identify which customer segments were actually profitable.
What we built
Built a customer data platform unifying Shopify, Klaviyo, and Meta Ads into a single customer view. Deployed a churn prediction model (XGBoost, 87% precision) and a real-time personalisation layer feeding segmented Klaviyo flows automatically.
"We finally know which customers are worth spending on. The churn model alone paid for the project in the first month."
23%
Reduction in churn
41%
Email open rate lift
3.2×
Marketing ROI
Logistics
Cloud Infrastructure + Automation6 weeks · India
Before us
The ops team had built a set of Python scripts that pulled data from each carrier's portal by hand. Scripts broke with every portal update, and the CFO was fielding carrier disputes monthly.
The problem
Manual reconciliation across 4 carrier systems consumed 35+ hours per week. Billing errors caused frequent disputes and the team had no live view of delivery performance or cost per shipment.
What we built
Deployed a unified S3 data lake with Lambda-based ingestion from all 4 carrier APIs. Built automated reconciliation with exception flagging and an ops dashboard showing live cost-per-shipment and on-time delivery by carrier. Infrastructure costs cut 40% by right-sizing EC2 and moving to Spot instances.
"We went from chasing carrier invoices every week to zero disputes in 6 months. The ops dashboard is now open on every morning standup."
35 hrs/wk
Manual work eliminated
40%
Infrastructure cost saved
Zero
Billing disputes, 6 months
What we build
Intelligent automation that handles repetitive decisions, compliance checks, and customer interactions. Your team focuses on work that actually needs humans.
Most AI demos work on clean data. Your production data isn't clean.
We build AI agents and retrieval systems with proper orchestration, hallucination guardrails, and failure-mode testing. Everything is validated against your actual data volumes and edge cases, not synthetic samples.
Reliable pipelines, warehouses, and dashboards your finance, ops, and marketing teams can trust. Built to handle your actual data volume, not a spreadsheet.
ETL pipelines that don't break at 2 AM.
We design, build, and hand over production data infrastructure complete with monitoring, documentation, and a 30-day support window. Analysts actually use what we build.
Why TryData
Freelancers bring one skill set with no structure. Large agencies send seniors to pitch and juniors to build. TryData is neither.
How we work
01
We review your stack or AI pipeline, identify the top failure risks, and tell you exactly what needs fixing. No sales deck, just an engineer's honest read.
02
Fixed scope, fixed price, fixed timeline. The person who scopes it builds it. No junior engineers swapped in after the pitch.
03
We build against your real data volumes and edge cases, not synthetic demos. Weekly progress updates, full transparency throughout.
04
Full documentation, runbooks, and a 30-day support window. You own the system and your team can operate it independently from day one.
Where we work
Remote-first delivery with contracts in USD, EUR, AED, or INR. NDAs standard. Daily written updates, so progress never depends on a meeting slot in your timezone.
IST
Home base. On-site possible in Mumbai; same-day response everywhere else.
GST · IST −1.5h
Full-day working overlap. Same-week kickoffs for Dubai and Abu Dhabi teams.
CET / GMT · IST −3.5 to −5.5h
Overlap through most of the European workday. GDPR-aware delivery from day one.
EST / PST · IST −10.5 to −13.5h
Daily overlap with North American mornings, plus written updates waiting when you wake up.
About TryData
After 10 years building data systems at enterprise scale, Dheeraj started TryData with one rule: the engineer who scopes the project ships the project. No handoffs to junior staff. No surprises after the pitch. Just systems that work.
30+ cloud systems shipped with zero production failures. $180K in documented client savings across 50+ engagements in FinTech, D2C, and logistics. We specialise in FinTech NBFCs and D2C brands because deep domain knowledge beats generalist delivery every time.
Client feedback
Month-end reporting cut from 3 weeks to 2 hours
"Excellent working with Dheeraj. Knowledgeable, professional, and hard-working. Deep expertise around AWS Services and building ETL pipelines. Very responsive throughout and will certainly rehire."
Jonathan Placa
Data Engineering Manager
FinTech Platform · New York, USA
Complex cloud provisioning fully automated with CDK
"Dheeraj demonstrated a deep understanding of cloud infrastructure and AWS services. His CDK expertise automated complex provisioning tasks and translated business requirements into maintainable architectures."
Karthik Gopal
Cloud Solutions Architect
Enterprise SaaS · Plano, USA
Enterprise AWS migration delivered with zero downtime
"His expertise with EC2 configuration, network connectivity, and database migration was outstanding. Reliable, responsive, and proactive in identifying issues, which ensured a smooth and successful delivery."
Vlad K.
AWS Migration Lead
Enterprise · Toronto, Canada
FAQ
Free audit
In 30 minutes we'll review your current data or AI setup, identify the top failure risks, and give you a prioritised fix list. No cost, no sales deck. Just an engineer's honest assessment.