012–4 weeks
RAG chatbot on your docs
An assistant that answers from your content, cites its sources, and says "I don't know" when it should.
- Ingestion & chunking
- Hybrid search + reranking
- Eval set & dashboard
- Deployed & handed over
RAG chatbots & AI agents that hold up in production.
Grounded answers with citations, agents that call your real tools, and evals that catch regressions before your users do. Scoped up front, shipped in weeks, handed over with docs.
Where most projects start
Three fixed-scope starting points
Pick one, or describe your problem and I'll scope it. Scope and price are agreed before any build begins.
023–6 weeks
Workflow agent
An agent that does real work in your systems — CRM, tickets, docs, databases — with a human in the loop.
- LangGraph / MCP tools
- Approval steps & guardrails
- Tracing & cost tracking
- Runbook for your team
031 week
RAG audit
Already have a chatbot that hallucinates or costs too much? I'll measure it and tell you exactly what to fix.
- Retrieval quality report
- Hallucination test set
- Cost & latency review
- Prioritised fix list
Client Feedback
What clients said after we shipped.
★★★★★
Very responsive and delivered great work. Thank you!
Would definitely hire again and recommend—ability to understand requirements and a talented individual.
Very knowledgeable and professional—would recommend hiring.
Top performer—will be working with them long term.
Very talented and great to work with.
Fantastic work, thanks!
Perfect!!
Services
Production AI agents, data platforms, cloud infrastructure, Python full-stack web, and Flutter mobile — scoped, shipped, and handed over with docs your team can run.
AI agents, agentic RAG & LLMOps
We ship production agentic AI and AI automation for business — not demos. Agents, agentic RAG, support copilots, and document intelligence with evaluation gates, MCP tooling, tracing, and governance controls.
- Production & agentic RAG: ingestion, vector search, reranking, citations, and grounded answers
- AI agents with LangGraph / MCP — multi-agent workflows, tool use, and human handoff
- Support & ops copilots — helpdesk, CRM, and internal knowledge with ticket deflection
- Document intelligence — contracts, invoices and KYC — extract, validate, write back
- LLMOps & evals — regression harnesses, quality gates, latency/cost dashboards, safety checks
- Governance-ready — audit trails, human-in-the-loop, and privacy-aware data handling with regional residency options
- Voice AI — Twilio + conversational agents for qualification, dispatch, and transfers
Data engineering & platform migration
Modern data stack delivery — pipelines that scale, dbt transforms you can trust, and phased warehouse cutovers with reconciliation across Snowflake, BigQuery, and more.
- Cloud data warehouse migration — dbt ports, parallel run, freeze/cutover, decommission
- Ingestion rebuild — Kafka sinks, Airbyte / Datastream CDC, batch ELT
- Orchestration — Cloud Composer / Airflow DAGs with retries, backfills, and alerting
- dbt modeling — incremental marts, tests, docs, and BI-ready views for Looker / Looker Studio
- Quality & reconciliation — row counts, aggregates, lineage, and cutover sign-off gates
- Streaming and batch — Kafka, Spark, GCS/S3 lakes, and warehouse cost controls
Cloud & DevOps
Run it anywhere. Deploy in minutes. Sleep at night. We build and operate infrastructure that scales—multi-cloud, on-prem, or hybrid.
- AWS, GCP, Azure—or all three with a unified approach
- Kubernetes, containers, and serverless—pick the right fit
- CI/CD pipelines that actually work—fast, reliable, observable
- Terraform, Pulumi, and IaC for reproducible environments
- Hardening, security audits, and compliance readiness
- Cost optimization, autoscaling, and disaster recovery
Python full-stack web development
End-to-end Python full-stack apps — FastAPI / Django backends, React or Next.js frontends, APIs, and databases. From MVP to enterprise, with AI copilots and workflows wired in where they pay off.
- Python backends — FastAPI, Django, Flask; REST and GraphQL APIs
- React, Next.js, and modern frontend with design systems and auth
- PostgreSQL, Redis, Supabase, and cloud-native deployment patterns
- AI in the product — chat, support copilots, and intelligent workflows
- Third-party integrations, real-time features, and partner-facing APIs
- Scalable architecture from prototype to production with docs your team can run
Mobile app development
Flutter apps for iOS and Android from a single codebase — booking flows, payments, document upload, and store release with production support.
- Cross-platform Flutter apps for iOS and Android
- App Store and Google Play release — TestFlight, listings, and version updates
- REST API integration, push notifications, and in-app payments
- Shipped production apps including Aadhya Self Drive
- Performance tuning, offline flows, and device-specific polish
- Clear handover with build pipelines and documentation
About Us
stackcone is a custom software and AI engineering studio. We design, build, and deploy production systems for startups and enterprise — one team from discovery to handover. Learn more about us.
We specialize in AI agent development, AI automation for business, agentic RAG with LLMOps evals, support and ops copilots, document intelligence, data engineering, Python full-stack web applications, cloud DevOps, and Flutter mobile. Every engagement comes with fixed scope, clear communication across time zones, privacy-aware delivery options, and documentation your team can run with.
- AI agents & AI automation — LangGraph / MCP agents, business workflows, human handoff
- Agentic RAG & LLMOps — retrieval, eval gates, tracing, cost/latency dashboards
- Support copilots & document AI — helpdesk/CRM copilots; contract and invoice extraction
- Data engineering & migration — Snowflake, BigQuery, dbt, Composer/Airflow, CDC, Kafka
- Python full-stack & mobile — FastAPI, Django, Next.js, Flutter iOS/Android
- Cloud & governance — AWS/GCP/Azure, audit trails, human-in-the-loop controls
Led by Amar Kumar, an AI and Python engineer with 10+ years shipping production systems.
10+ years experience
·
18 verified Upwork reviews
Why teams hire stackcone
Startups and enterprise teams hire stackcone when they need production systems—not slide decks or proof-of-concept demos. We work remote-first worldwide, align scope before writing code, and hand over runbooks so your team owns the stack after launch.
Healthcare & clinical data
FHIR pipelines, AthenaOne integrations, and privacy-aware cloud analytics for specialty practices that need research and AI review outside the native EHR UI. See our clinical data platform brief.
Legal, property & regulated search
Multi-agency record search, landlord due diligence, and marketing attribution pipelines where data quality and audit trails matter. Explore NYC property records search and BigQuery attribution briefs.
SaaS & AI-native products
Python full-stack platforms, agent orchestration, and fractional CTO engagements for dual-product SaaS teams shipping AI features under real user load. Browse the portfolio and AI SaaS platform brief.
Field service & voice automation
Voice AI for lead qualification, SMS dispatch loops, and CRM-integrated workflows when a solo operator must scale without living on the phone. Read the voice lead qualification and field-service dispatch briefs.
Remote, without the time-zone pain
We work remote-first with teams worldwide. Calls happen in the hours that overlap with yours, and written updates and milestone demos fill the gaps, so work moves forward while you sleep.
Time-zone overlap
Calls in the overlapping hours, plus written updates and milestone demos you can review in your own time.
GDPR-aware delivery
Data minimisation, regional hosting when required, audit trails and human oversight. Read the GDPR guide for AI agents.
Simple contracts
Hire through Upwork or contract with us directly after a scoping call. Scope and price agreed first.
Full handover
Source code, deployment guide, runbooks and a walkthrough, so your team owns what we build.
Our Process
01
Discovery & scope
Align on goals, data, and constraints. Agreed scope and milestones before we build.
02
Design & build
Build in line with scope. Check-ins, demos, and iterations so you can steer.
03
Deploy & handover
Deploy and hand over with docs, runbooks, and monitoring. Your team owns and extends it.
Stack we work on
Technologies and platforms we use to build your solutions — including Flutter for iOS and Android mobile apps.
Cloud
Languages
Backend & APIs
Frontend
Mobile
Data
AI & ML
DevOps & Infrastructure
Latest engineering guides
In-depth tutorials on production RAG, AI agents, LLMOps, data engineering, and software delivery — from the stackcone blog. Browse solution briefs, the portfolio, or start with these high-intent builds: multi-agent SEO pipeline, NYC landlord records search, and AI agents + MCP for data engineering.
Will AI Take Coding Jobs?
From GPT-1 through cloud agents — which coding roles are at risk, what mass displacement would do to the economy, and the more likely middle path.
NVIDIA and the AI Memory Wall
NVIDIA Rubin raised HBM4 bandwidth, but DRAM shortages may cut Rubin Ultra memory. Interactive KV-cache calculator and how the memory wall changes RAG.
The DRAM Supercycle
AI reallocated DRAM wafers to HBM and server DDR5. Why contract prices jumped, consumer RAM starved, and how RAG teams should buy memory.
SpaceX Starship and the Falcon Drawdown
SpaceX plans fewer Falcon 9 flights as Starship takes Starlink V3. Flight 13, Artemis gaps, and what operators should assume about rides to orbit.
The AI Bubble Debate
Capex, HBM shortages, and bubble skepticism can all be true. A product test for teams that do not want to underwrite unused GPU racks.
AI Agent Testing and Evaluation Strategies
Production AI agent testing — golden dataset eval, unit tests for tools, trace replay, regression gates, and continuous monitoring patterns for reliable agent deployment.
How to Build a Cursor-Like AI Coding Agent
Step-by-step guide: tool-calling harness loop, SSE streaming, context compaction, permissions, and subagents — with full pseudocode from LiveCode.
Auto Model Routing Without an LLM Classifier
Auto model routing without an LLM classifier — heuristic tier selection, regex signals, post-retrieval upgrades, and pytest-tested routing for production RAG chat.
Find us online
Connect with stackcone on LinkedIn, Clutch, Wellfound, GoodFirms, and Upwork.
Frequently asked questions
What custom software development services does stackcone offer?
We build production AI agents and AI automation for business, agentic RAG with LLMOps evals, support and ops copilots, document intelligence, data engineering, Python full-stack web (React, Next.js, FastAPI, Django), Flutter mobile, and cloud DevOps on AWS, GCP, and Azure — with fixed scope and full handover.
Do you work with international clients?
Yes. We work remote-first with companies worldwide and plan calls in the hours that overlap with your team. Milestones are agreed in writing, and every project ends with documentation your team can run. How an engagement works.
How do I hire AI developers or a custom software team at stackcone?
Use our contact form, hire us on Upwork, or message us on LinkedIn. We respond within 24 hours with discovery and fixed-scope next steps.
Do you build AI agents for business automation?
Yes — production AI agents and multi-agent workflows with LangGraph, MCP tool servers, human handoff, evaluation gates, and tracing so agents run real business tasks. Browse solution briefs for agent architectures.
Can you build a production RAG or agentic RAG system?
Yes — document ingestion, vector search, reranking, tool-using retrieval, evaluation, monitoring, and deployment. See our portfolio and blog for case studies and technical guides on production RAG.
Do you do Python full-stack development?
Yes — FastAPI, Django, and Flask backends with React or Next.js frontends, PostgreSQL, REST/GraphQL APIs, and cloud deploy on AWS, GCP, and Azure. AI features can ship inside the same product stack.
How do you handle data privacy and AI governance?
Privacy-aware by design: minimize data processed, support regional cloud residency when required, and ship agents with human-in-the-loop controls, audit trails, and access boundaries. We align to your compliance requirements — we do not claim certifications we do not hold. See our privacy policy.
Do you migrate cloud data warehouses and data platforms?
Yes — phased migrations with dbt transform ports, Kafka/CDC ingestion rebuilds, Airflow/Composer orchestration, historical backfill, parallel-run reconciliation, and cutover across warehouses like Snowflake and BigQuery. See our data platform migration brief.
Can you add evaluation and LLMOps to our AI agents?
Yes — eval harnesses, regression gates, tracing, cost and latency dashboards, and safety checks so agents and RAG systems ship with measurable quality. Browse solution briefs for agent and RAG architectures.
What is the difference between a RAG chatbot, a workflow agent, and a copilot?
A RAG chatbot answers from your documents with citations and an explicit “I don’t know” path. A workflow agent takes actions in your tools — CRM, tickets, databases — with approvals and tracing. A copilot sits inside an existing product and assists a person in place. Most teams start with RAG, add tools when the bot needs to do work, and ship a copilot when the UI already exists.