Forward-Deployed AI · Custom Workflow Automation · Pune, India

AI Agents & Custom Workflow Automation for Your Business

Forward-deployed engineers who embed in your org, discover inefficiencies, and ship AI-powered automation that fits your exact workflows.

Industries Served

Financial Services · SaaS · AI/ML · Healthcare · E-Commerce

Engagement Models

Forward-Deployed Sprints · Dedicated Teams · Full GCC Build-Outs

Headquartered In

Pune, India — serving global enterprises across the US, UK, and Europe

Why WorksNet

We Build AI That Fits Your Workflow — Not the Other Way Around

Most AI vendors hand you a product and expect you to change how you work. We take the opposite approach: our engineers embed in your team, map your actual workflows, then build custom automation that integrates seamlessly with the tools and processes you already have.

Problem-First, Not Product-First

We don't sell a platform. We identify the specific inefficiencies costing you time and money, then engineer targeted solutions using LLMs, custom agents, or traditional automation — whichever fits best.

Full Ownership — Code, Data, People

Whether it's automation we build or a GCC team we help you hire, you own everything. No vendor lock-in, no recurring SaaS fees for custom work. Your IP is yours.

India's Engineering Talent, Your Dedicated Team

Through our GCC service, you get a fully integrated engineering team in Pune that operates as part of your company — not a contractor, not an agency, your own team with your culture.

Weeks to Value, Not Quarters

Our forward-deployed model means engineers are productive from day one. Discovery, prototyping, and first deployments happen in the first 2-4 weeks of engagement.

How Engagements Typically Look

Every engagement is different, but here's a typical trajectory for a forward-deployed automation project:

Week 1–2

Engineer embeds, maps workflows, identifies top automation candidates

Week 3–4

First automation prototype built, tested with real data, iterated on feedback

Week 5–8

Production deployment with monitoring, additional workflows automated in parallel

Ongoing

Iteration, new use cases, knowledge transfer to your internal team

Our Approach

Simple Process, Exceptional Outcomes

We embed, discover, and deploy — shipping custom AI automation in weeks, not quarters.

01

Embed & Discover

Our engineers join your team — same Slack channels, same standups, same codebase access. They observe how your team works, identify repetitive manual processes, and map the workflows where AI automation would have the highest impact.

02

Prototype & Validate

We build a working prototype of the highest-impact automation within the first 2-3 weeks. Not a mockup or a proposal — real code, running against real data, that you can test and give feedback on immediately.

03

Ship & Iterate

Production deployment with monitoring, error handling, and alerting. Then we iterate: improve accuracy, add edge cases, expand to adjacent workflows. Knowledge transfer happens continuously so your team can maintain and extend the system.

Technical Expertise

The Stack Behind Our Solutions

We pick the right tool for the problem — not the other way around. Our engineers are practitioners across the AI and data engineering ecosystem.

LLM Orchestration

Multi-model systems using OpenAI, Anthropic, and open-source models. We route tasks to the right model based on cost, latency, and quality requirements.

Custom AI Agents

Autonomous agents built with tool-calling, retrieval-augmented generation, and structured output. Not chatbots — real task-completing systems.

Data Engineering

Batch and streaming pipelines on AWS/GCP. Kafka, Spark, dbt, Airflow — designed for reliability and observability at production scale.

Full-Stack Delivery

React, Next.js, Python, FastAPI, PostgreSQL, Redis. Clean architecture, CI/CD from day one, infrastructure-as-code on every project.

Problems We Solve

Real Scenarios, Real Outcomes

A sample of the types of problems our forward-deployed engineers have tackled across industries.

B2B SaaS

A SaaS company's operations team was spending 30+ hours per week manually classifying and routing support tickets across 12 product areas.

What we built

We built a multi-label classification agent using fine-tuned embeddings that auto-routes tickets with routing accuracy above human operators — reducing triage time to near-zero.

Fintech

A fintech startup needed to build a 50-person engineering team in India but had no local presence, legal entity, or recruitment pipeline.

What we built

Full GCC setup: entity incorporation, office lease, HR systems, and a recruitment engine that filled all 50 roles within 14 weeks — engineers integrated into their existing sprint cycles.

AI / ML

An AI company training foundation models needed to scale from 50K to 500K annotations per month while maintaining strict quality benchmarks for RLHF data.

What we built

Designed a hybrid human-AI annotation pipeline with multi-layer QA, active learning for pre-labeling, and domain-specific annotator training that hit target volume without quality regression.

Ready to Automate Your Workflows?

From a single AI agent to full-scale workflow automation, we embed, build, and ship — tailored to how your team works.