AI-native consulting

We turn into operating advantage.

Sunday Labs is a boutique consulting firm for AI and data transformation. We design the strategy, build the data foundations and ship production AI, alongside your team, in weeks rather than quarters.

Book a discovery call → See what we do
Senior-only teams Production, not slideware You own the IP
labs-agent ~ engagement.plan running
Data readiness0%
Use cases ranked0
Time to pilot--

Trusted by

Fast-growing teams across fintech, logistics, healthcare and commerce build with Sunday Labs.

  • PorterLogistics
  • BharatPeFintech
  • TeamLeaseStaffing
  • AXISMUTUAL FUNDAsset management
  • Consumer tech
  • DELHIVERYLogistics
  • Apollo24|7Healthcare
  • indifiLending
  • GradRightEdtech
  • SINARMASConglomerate
  • AwanTunaiFintech
  • pepperfryE-commerce
  • GroMoFintech
  • KhelGroupGaming
  • + many moreBecome the next →

Built on

AnthropicOpenAIGoogle CloudAWSMicrosoft AzureDatabricksSnowflakedbtLangGraphKubernetesTerraformHugging Face

Why we exist

Most AI programmes stall between the pilot and the P&L. Not because the models are weak, but because the data is scattered, the workflows are unchanged and nobody owns the outcome. We fix all three, and we stay until it works.

What we do

Everything between ambition and production.

Six practices, one team. Pick a single engagement or let us run the full transformation end to end.

01

GenAI & Agentic Systems

Copilots, retrieval systems and autonomous agents wired into your real tools and data. Evaluated, guard-railed and monitored like any other critical system.

  • RAG
  • Agents
  • Evals
  • Tool use
  • Fine-tuning
02

AI Strategy & Roadmaps

We find where AI moves your numbers, size the value, and sequence a roadmap your board and your engineers can both believe in.

  • Opportunity mapping
  • Business cases
  • Operating model
03

Data Platforms & Engineering

Modern lakehouses, clean pipelines and governed semantic layers. The unglamorous foundation that makes every model downstream actually useful.

  • Lakehouse
  • ELT
  • Data quality
  • Streaming
04

Analytics & Decision Intelligence

Forecasting, pricing, churn and demand models, plus dashboards people genuinely open. Answers delivered where decisions get made.

  • Forecasting
  • ML
  • BI
  • Experimentation
05

MLOps & AI Engineering

CI/CD for models, feature stores, observability and cost controls, so AI stays reliable, auditable and affordable after launch day.

  • LLMOps
  • Monitoring
  • Cost control
06

Digital Transformation & AI Governance

Process redesign, change management and responsible-AI frameworks aligned with the EU AI Act, DPDP Act and your internal risk appetite. We make sure the new tools actually change how work gets done.

  • Process redesign
  • Change
  • Responsible AI
  • Training

Managed services

We don't just build it. We run it.

Cloud, infrastructure, DevOps, QA and release management, operated 24x7 against clear SLAs by the same team that designs your AI and data platforms.

24x7 on-callSLA-backedAWS · Azure · GCP
Explore managed services →
Cloud Management & FinOps Infrastructure & Platform Engineering DevOps & CI/CD Release Management QA Management & Test Automation SRE, Monitoring & 24x7 Support Security & Compliance Operations Digital Transformation & Modernisation Application & Data Platform Support

Technology we work with

Fluent in the modern AI and cloud stack.

We are platform agnostic. We pick the right model, cloud and tooling for your problem, and work inside the stack you already run.

  • AAWS
  • MMicrosoft Azure
  • Google Cloud
  • Cloudflare
  • DigitalOcean
  • Vercel
  • OOpenAI
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Mistral AI
  • DeepSeek
  • Hugging Face
  • NVIDIA
  • Ollama
  • Replicate
  • LangChain
  • LangGraph
  • LLlamaIndex
  • PPinecone
  • Qdrant
  • Weights & Biases
  • MLflow
  • PyTorch
  • TensorFlow
  • scikit-learn
  • n8n
  • Streamlit
  • Databricks
  • Snowflake
  • BigQuery
  • Apache Spark
  • Apache Kafka
  • Apache Airflow
  • ddbt
  • PostgreSQL
  • MongoDB
  • Redis
  • Elasticsearch
  • Terraform
  • Kubernetes
  • Docker
  • Helm
  • GitHub Actions
  • Argo CD
  • GitLab
  • Jenkins
  • Ansible
  • Vault
  • Datadog
  • Grafana
  • Prometheus
  • OpenTelemetry
  • PagerDuty
  • Sentry
  • PPlaywright
  • Cypress
  • Selenium
  • Postman
  • SonarQube

Product names and logos are trademarks of their respective owners and are shown to indicate technologies we work with. Their use does not imply partnership or endorsement.

How we work

From first call to first model in production.

A tight, repeatable loop. Every phase ends with something you can use, not just something you can read.

01

Discover

Weeks 1 to 2

Stakeholder interviews, data audit and a ranked backlog of AI use cases scored on value, feasibility and risk.

02

Design

Weeks 2 to 3

Target architecture, success metrics and an evaluation plan agreed before a single line of production code.

03

Build

Weeks 3 to 8

Small senior squads ship in weekly increments with your team embedded, so knowledge transfers as we go.

04

Scale

Ongoing

Hardening, monitoring and rollout across teams, then a clean hand-off or a lean run-and-improve retainer.

Engagement at a glance

A typical 8-week programme

Week 1
W1W2W3W4W5W6W7W8W9+
Discover
Design
Build
Scale
Milestones
  1. Ranked use-case backlogValue, feasibility and risk for each idea
  2. Architecture sign-offTarget stack, metrics and eval plan
  3. Pilot live in productionReal users, real data, measured impact
  4. Rollout and hand-off planRunbooks, training and ownership
2 to 4senior people per squad
Weeklydemos, never monthly decks
1 metricagreed upfront, tracked to the end
0 wksTypical time from kickoff to a production pilot
0%Of code, models and IP owned by you
0 teamStrategy, data and engineering under one roof
0Vendor lock-in. We are platform agnostic by design

Where we play

Deep in the industries where data is the product.

Financial Services

Credit risk, fraud detection, KYC automation and AI-assisted operations.

Retail & D2C

Demand forecasting, personalisation, pricing and catalogue intelligence.

Healthcare & Life Sciences

Clinical documentation, claims processing and patient-journey analytics.

Manufacturing & Supply Chain

Predictive maintenance, quality inspection and inventory optimisation.

SaaS & Technology

AI features inside your product, usage analytics and support automation.

HR & Talent

Screening, matching, workforce planning and people analytics at scale.

Engagement blueprints

What a Sunday Labs engagement looks like.

Three of the patterns we are asked for most, with the outcome each one is built to hit.

Operations

Agentic back office

Agents that read, classify and act on invoices, tickets and emails, with humans approving only the exceptions.

60%+target reduction in manual handling
Data

Single source of truth

Consolidating a sprawl of spreadsheets and databases into one governed lakehouse with metrics everyone trusts.

1semantic layer powering every dashboard and model
Knowledge

Enterprise copilot

A secure assistant grounded in your policies, contracts and wikis, with citations, access control and evals.

Minutesinstead of hours to find the right answer

Outcomes shown are engagement targets, not guarantees. Actual results depend on your data, scope and adoption.

How we think

Built by operators, not just advisors.

We ship our own AI product every week. That changes how we consult.

01

Value before models

Every engagement starts with a metric that matters to the business. If we cannot measure it, we do not build it.

02

Data is the moat

Models are becoming a commodity. Your proprietary data, cleaned and connected, is what compounds.

03

Evaluate everything

We treat prompts and models like code: versioned, tested and measured against real-world evals.

04

Leave you stronger

We pair with your people, document everything and aim to make ourselves unnecessary.

FAQ

Questions we hear a lot.

Who actually works on my project?
A small senior squad, personally overseen by our founder. The lead engineer and architect always comes from companies like Amazon, Google, Microsoft, Uber or Meta, and the people you meet during scoping are the ones who build and ship. Meet the team behind the work.
What does a typical engagement look like?
Most clients start with a two-week discovery sprint that produces a ranked use-case backlog and an architecture plan. From there we usually build a production pilot in four to six weeks, then scale it across the business.
Do you work with our existing cloud and tools?
Yes. We are platform agnostic and work across AWS, Azure and Google Cloud, with warehouses like Snowflake, Databricks and BigQuery, and with both commercial and open-weight models.
How do you handle data security and privacy?
We work inside your environment wherever possible, follow least-privilege access, sign NDAs and data processing agreements as standard, and design for compliance with applicable law including India's DPDP Act and GDPR.
Who owns what we build?
You do. Unless we agree otherwise in writing, all code, models, prompts and documentation created for you during the engagement belong to you once invoices are settled.
How do you price?
Fixed-fee sprints for discovery and pilots, and monthly retainers for ongoing build and run. We will always give you a clear scope and number before any work begins.

Ready to make AI pay off?

Tell us where you are. We will come back within one business day with a point of view, not a sales deck.

Start a conversation → sales@sundaylabs.io

Contact

Let's build something that ships.

Pick a time for a discovery call. You will speak with a founder, not a sales team.

Sales
sales@sundaylabs.io
Support
support@sundaylabs.io
Office
Headquarters: Gurugram, India

Pick a time on our booking page, or email sales@sundaylabs.io.

Global presence

Headquartered in India. Working worldwide.

Teams and clients across seven regions, with overlapping hours so work moves forward around the clock.

IndiaUSUKMENAIndonesiaSingaporeAustralia
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