Intelligent Automation. Scalable Solutions. Built for the Global Frontier.

Reliable automation for teams that need to move fast.

4 Global offices
3 Continents
99.9% Uptime
24/7 Support

Built for your industry.

We understand the unique challenges of your sector — and we know how to solve them.

Healthcare & Hospitals

Patient data silos, manual reporting, and compliance overhead slow down care. We build secure data platforms, automate admin workflows, and surface real-time insights for clinical and operational teams.

  • Patient analytics
  • Compliance reporting
  • Workflow automation
  • EHR integration
Hospital Management System →

Education & Schools

From student information systems to fee management and academic analytics — we modernize school and university operations so administrators spend less time on paperwork and more time on outcomes.

  • Student analytics
  • Fee automation
  • ERP integration
  • Attendance reporting
School ERP for Nepal → Student & parent app →

Banking & Finance

Legacy systems, manual reconciliation, and slow reporting cost money. We modernize data infrastructure, automate financial workflows, and deploy AI for fraud detection and customer intelligence.

  • Fraud detection
  • Regulatory reporting
  • Data warehousing
  • Process automation
Banking automation Nepal →

Government & Public Sector

We help government agencies digitize paper processes, connect siloed departments, and build dashboards that give decision-makers real-time visibility — without disrupting existing systems.

  • Digital transformation
  • Workflow automation
  • Reporting dashboards
  • Legacy modernization
Government digitization Nepal →

Large Corporates & Enterprise

Disconnected tools, manual reporting, and slow deployments hold enterprise teams back. We embed as a senior technical partner — delivering data platforms, AI integrations, and automation at scale.

  • Enterprise data platform
  • AI integration
  • DevOps transformation
  • Cost optimization
Enterprise AI rollout roadmap → Data platform consolidation →

Construction & Real Estate

Project cost overruns, delayed reporting, and disconnected site data are avoidable. We build dashboards, automate procurement workflows, and connect your project management tools into one platform.

  • Project analytics
  • Cost tracking
  • Procurement automation
  • Document management
Construction tech buyer's guide → Real estate data platforms →

Logistics & Shipping

From fleet tracking to warehouse automation and supply chain analytics — we help logistics companies eliminate manual processes, gain real-time visibility, and reduce operational costs with data and AI.

  • Supply chain analytics
  • Fleet tracking
  • Warehouse automation
  • Route optimization
  • Shipment visibility
Logistics & Shipping solutions →

Real systems,
shipped in production.

A few engagements that show how we move from brief to measurable outcome.

Fintech 2025

Real-time fraud-signal pipeline for a payments processor

Problem. Risk team was reviewing fraud cases 6+ hours after the transaction, missing the chargeback window.

Approach. Kafka + Flink streaming pipeline feeding a feature store; rules engine + lightweight model scoring at ingestion.

Outcome. Detection latency dropped from hours to seconds. Recovered chargebacks paid for the engagement in the first quarter.

12×faster detection
$1.4Mchargebacks recovered (Y1)
  • Kafka
  • Flink
  • Feast
  • Snowflake
SaaS · B2B 2025

RAG-powered support copilot deployed across 4 product teams

Problem. Tier-1 support was drowning in repetitive tickets; resolution time creeping up quarter over quarter.

Approach. Retrieval pipeline over docs + past tickets, GPT-4o-mini for drafting, human-in-the-loop UI, evals before every release.

Outcome. 41% of tickets now closed by the copilot with no human edits. CSAT held flat while volume per agent dropped.

41%tickets auto-resolved
2.8×agent throughput
  • LangChain
  • pgvector
  • OpenAI
  • LangSmith
Logistics 2024

Migrated 14-year legacy ETL to a modern data platform

Problem. Nightly SSIS jobs ran 9+ hours; one failure meant analysts couldn't open the dashboards in the morning.

Approach. Airflow + dbt over Snowflake. Phased cutover, parity tests against legacy outputs, runbook + IaC handover.

Outcome. Full refresh now finishes in 38 minutes. Failure recovery measured in minutes, not days.

14×faster nightly runs
99.7%pipeline success rate
  • Airflow
  • dbt
  • Snowflake
  • Terraform

Case studies are anonymised representative engagements. Real client names available on request under NDA.

The DevOps team
you always wanted.

pdpspectra is an international AI, data, and DevOps consultancy with offices in Boston, London, Sydney, and Kathmandu. We're a lean, senior-level team of data engineers, AI specialists, and DevOps engineers who help businesses worldwide unlock the value in their data — from early-stage startups to large enterprises and public sector organizations.

At pdpspectra, we bridge the gap between raw data and real business impact. Whether you're building your first data platform, integrating AI into your product, or automating your operations, we get you there fast.

Data-driven We turn data into decisions
AI-powered Practical AI that ships to production
Built to scale Infrastructure that grows with you

Where we work.

Senior engineers across four locations, delivering for clients worldwide.

Americas

Boston

United States

EST (UTC−5)

Our US base for North American clients. Covering AI strategy, enterprise data, and cloud architecture engagements across the Americas.

Europe

London

United Kingdom

GMT (UTC+0)

European hub for financial services, government, and enterprise clients across the UK and EU.

Asia Pacific

Sydney

Australia

AEST (UTC+10)

Asia-Pacific base serving Australian and Southeast Asian clients across healthcare, logistics, and enterprise sectors.

Engineering HQ · South Asia

Kathmandu

Nepal

NPT (UTC+5:45)

Our engineering hub. Home to our core engineering team serving clients across South Asia and globally.

Three ways to work
with us.

From a short discovery sprint to an embedded team. Fixed deliverables, no surprise bills.

Best for first projects

Discovery sprint

2 weeks · fixed fee

A focused audit and roadmap. You leave with a concrete plan you can execute with us — or anyone else.

  • Current-state architecture review
  • Prioritised opportunity backlog
  • Reference architecture diagrams
  • Cost & effort estimates per initiative
  • 90-min stakeholder readout
Book a discovery sprint
Most popular

Build engagement

6–16 weeks · milestone-based

We design, build, and ship a defined system end-to-end. You get a working production deployment, plus the docs and IaC to maintain it.

  • Everything in Discovery
  • Production implementation
  • Infrastructure as code (Terraform)
  • Observability + runbooks
  • Team handover & training
  • 30-day post-launch support
Scope a build
For scaling teams

Embedded team

3+ months · monthly retainer

Senior engineers embedded in your stand-ups. Capacity to ship multiple workstreams alongside your in-house team.

  • 1–3 engineers full-time
  • Weekly delivery cadence
  • Shared backlog & ownership
  • Pause / scale anytime
  • Quarterly architecture review
Talk to us

From brief to deployment,
without the noise.

01

Discovery

We audit your current stack, understand your pain points, and map the path forward.

02

Design

Architecture diagrams, IaC scaffolding, and a clear delivery roadmap before we write a single line.

03

Build

We implement in sprints with full visibility — code reviews, docs, and handover included.

04

Operate

Ongoing support, monitoring, and optimization. We stay in the picture as long as you need us.

Senior engineers,
shipped outcomes.

They didn't try to sell us a platform — they fixed what was actually broken and left us with infrastructure we own. The runbook alone has paid for itself twice.
Frank Valiyev Head of Data · Jokxen Data · United States
We hired pdpspectra for what was supposed to be a six-week proof-of-concept on RAG. They shipped a production system in eight, with evals our internal team is still using to gate releases.
Andrei Istrate VP of Engineering · United Kingdom
The kind of partner you wish you'd hired six months earlier. Tight scope, no theatre, and they actually documented the things they built.
Bastien Rainovski CTO · Hult · Australia

Common questions,
straight answers.

pdpspectra has offices in Boston (US), London (UK), Sydney (Australia), and Kathmandu (Nepal). We serve clients worldwide across healthcare, finance, education, logistics, government, and technology sectors. Whoever you reach first hands off to whichever office best matches your timezone and domain.

Yes — in Nepal and internationally. We build patient data platforms, automate hospital admin workflows, and integrate AI into healthcare operations for hospitals and clinics. We work to local compliance standards (MoHP in Nepal, HIPAA-equivalent for international engagements) and integrate with existing hospital management systems rather than replacing them.

Yes. We help schools and universities — in Nepal and globally — modernize with student information systems, fee automation, attendance tracking, and academic analytics. We integrate with existing tools or build custom platforms tailored to the local education sector. Nepal is a particular specialty.

Yes. We help government agencies and public sector organizations in Nepal digitize paper processes, automate workflows, and build reporting dashboards. We understand local procurement processes and can work within government IT frameworks.

Yes. We help logistics companies eliminate manual processes and gain real-time visibility — fleet tracking, warehouse automation, supply chain analytics, route optimization, and shipment-status dashboards. Typical wins: faster dispatch decisions, lower fuel and labor costs, and one source of truth across the systems that don't currently talk to each other.

Yes. Our four offices — Boston, London, Sydney, and Kathmandu — span EST through AEST, so engagements are run from whichever office best overlaps with your working hours. Standups, code reviews, and incident response are scheduled around your timezone, not ours.

Absolutely. Many of our clients are traditional businesses — hospitals, schools, financial institutions, and government agencies — who want to modernize without hiring a full in-house tech team. We handle the technical complexity and communicate in plain language throughout. You don't need to understand data pipelines to work with us; you just need a clear business problem.

Yes — in fact, non-tech businesses often see the biggest ROI from data and automation work because the baseline is lower. If your team is still using spreadsheets, manual approvals, or disconnected software, there's significant opportunity to save time and reduce errors. We scope every engagement around your business outcomes, not technical deliverables.

AI can automate repetitive tasks, surface insights from your data, power intelligent customer experiences, and help your team make faster decisions. We implement practical AI solutions — from LLM-powered internal tools and customer chatbots to predictive analytics and automated workflows — that deliver measurable ROI without years of R&D.

Data engineering is the practice of building systems that collect, store, and transform your data so it can be used for analytics, reporting, and AI. If your team spends time manually exporting spreadsheets, can't trust your data quality, or wants to use AI but doesn't have clean data to work with — you need data engineering. We build pipelines using Airflow, dbt, Spark, Snowflake, Databricks, and ClickHouse.

We automate anything that involves repetitive manual steps — data syncs between tools, report generation, approval workflows, alert systems, and scheduled jobs. We use n8n, Apache Airflow, custom APIs, and native integrations to connect your existing stack without replacing it. Most automation projects save teams 10–30 hours per week.

MLOps (Machine Learning Operations) is the practice of deploying, monitoring, and maintaining ML models in production reliably. Most businesses can train a model — the hard part is keeping it running accurately in the real world as data changes. We set up ML pipelines, model registries, drift monitoring, and retraining workflows using MLflow, Kubeflow, and AWS SageMaker.

Both. We work with early-stage startups building their first data platform or integrating AI quickly, and with growing companies scaling their infrastructure or modernising legacy systems. Our lean team structure means we move fast without the overhead of a large consultancy. If you have a specific data, AI, or automation problem, we can help regardless of company size.

We work across AWS, Google Cloud Platform (GCP), and Microsoft Azure. We also support hybrid and multi-cloud setups. Most of our data and AI tooling is cloud-agnostic — we choose the right platform based on your existing stack, budget, and workload requirements.

Python Apache Airflow dbt Apache Spark Snowflake Databricks ClickHouse BigQuery LangChain OpenAI PyTorch MLflow Kubeflow AWS SageMaker Kubernetes Terraform GitHub Actions ArgoCD Grafana AWS GCP Azure Python Apache Airflow dbt Apache Spark Snowflake Databricks ClickHouse BigQuery LangChain OpenAI PyTorch MLflow Kubeflow AWS SageMaker Kubernetes Terraform GitHub Actions ArgoCD Grafana AWS GCP Azure

Ready to build with data and AI?
We're in your timezone.

Tell us about your project. We'll respond within 24 hours.

[email protected]
🇺🇸 Boston 🇬🇧 London 🇦🇺 Sydney 🇳🇵 Kathmandu