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Four ways in. Start with the cheapest one.

Most people arrive holding a proposal they cannot evaluate. The right first step is almost never the big build — it is a paid review that tells you what the work genuinely requires, so that every later decision is made with a number you trust.

Prices below are real ranges, not “contact us”. The final number is fixed in writing before work starts and does not move unless you change the scope.

01 · Advisory · fastest to start

Architecture review & advisory

Find out what it should cost before anyone builds it.

₹25k – ₹75k1–2 weeks

You have a quote, a vendor proposal, or an internal plan, and no independent way to judge it. I read the requirement, map what actually needs building, and tell you where the estimate is real and where it is padding — in writing, with a recommended architecture you can hand to whoever builds it, including someone other than me.

What you get

  • Written architecture document with a system diagram
  • Build-versus-buy assessment per component
  • An honest cost and timeline range for the work
  • A review of any vendor proposal you already hold
  • Two follow-up calls after delivery

“Why pay for advice from someone who wants to build it?”

Because the document is yours regardless of who builds it, and I will tell you when a component should be bought rather than built. If the answer is that you do not need a custom system, that is the answer you get — it is the cheapest possible outcome for you and the one that makes the advice worth paying for.

Talk about architecture review & advisory →
02 · AI · most common request

AI integration into what you already run

Agentic RAG and LLM workflows bolted onto your existing systems.

₹1.5L – ₹6L3–8 weeks

Most businesses do not need to replace anything to get value from AI. They need their own documents searchable and answerable, their repetitive document handling automated, or a workflow that currently costs three people a day made to run on its own. This is grounded retrieval over your data, wired into the systems you already have, with citations so an answer can always be traced back to its source.

What you get

  • Retrieval pipeline over your documents or database
  • Answers that cite their source, with a refusal path when retrieval finds nothing
  • Integration into your existing stack — no rip and replace
  • Cost controls: model routing and caching, so spend is predictable
  • Handover documentation and a walkthrough with your team

“How do we know it will not make things up?”

Because it answers only from what it retrieved, and every answer carries a citation you can open. When retrieval finds nothing above the threshold, it says so instead of guessing. This is the part most AI demos skip and the part I build first — you will see it refuse to answer during the demo.

Talk about ai integration into what you already run →
03 · Build · you own the code

Fixed-scope custom systems

The internal tool, dashboard, or automation, built to a fixed price.

₹2L – ₹10L4–12 weeks

Scoped, quoted, and built to a written specification. Internal tools, operations dashboards, customer portals, integrations between systems that do not talk to each other. You get the source code and the deployment, not a licence — which means you can hire anyone to maintain it afterwards, including nobody.

What you get

  • Complete source code in your repository, under your ownership
  • Deployed and running on infrastructure you control
  • Technical documentation and a handover session
  • Fixed price agreed before work starts — scope changes are quoted, never assumed
  • 30 days of defect fixes after handover at no cost

“What happens if you become unavailable halfway through?”

The code lives in your repository from the first commit, not mine, and it is documented as it is written rather than at the end. Payment is staged against delivered milestones, so you are never paid ahead of work. If everything stopped tomorrow you would hold working, documented code up to the last milestone and owe nothing further.

Talk about fixed-scope custom systems →
04 · Systems · largest engagements

ERP and business system replacement

Build the twenty per cent of the ERP you actually use.

₹6L – ₹25L3–9 months, delivered in phases

Enterprise ERP is priced for enterprises, and most mid-sized businesses use a fraction of what they license — while paying per seat, per year, forever, for the rest. The alternative is building precisely the modules you use, integrated with the accounting or compliance systems you must keep, and owning the result outright. Not always the right answer; the architecture review exists to establish whether it is yours.

What you get

  • Module-by-module scope agreed before anything is built
  • Migration plan and data import from your current system
  • Integrations with the tools you are keeping
  • Role-based access, audit trails, and reporting
  • Staff training sessions and written operating documentation
  • Phased delivery — each phase usable on its own

“Is replacing a working ERP not an enormous risk?”

Yes, which is why it is phased and why the first conversation is an architecture review rather than a proposal. Each phase is usable on its own and runs alongside your existing system until you choose to switch. If the review concludes that you should stay where you are and integrate instead, that is what the document will say.

Talk about erp and business system replacement →

How comparable problems actually went

One case per service. The only number quoted anywhere is real, and every claim opens into its full write-up.

IntegrateXproves · Fixed-scope custom systems

The save button that nearly sank a product

The problem
A node-based workflow builder was persisting the editor's entire UI state on every save. Payloads ballooned, saves crawled, and real-time sync lagged behind the canvas the moment workflows got big enough to matter.
The decision
Draw a hard serialization boundary: a schema-aware adapter that maps rich React Flow objects to compact domain records, so the database stores the workflow — not the view. The client reconstructs presentation state for free.
What it bought
Workflow payloads shrank by 94%, round-trip lossless. Saves and loads became effectively instant, and the state-sync churn disappeared — an architecture call, not a bigger server.
React FlowZustandTypeScriptNode.js
The 94% decision, in full →The adapter pattern itself →
Police RAG Agentproves · AI integration into what you already run

Retrieval over documents where a wrong answer isn't an option

The problem
A question-answering system over police and legal documents — a domain where an invented citation or a confidently wrong answer is worse than no answer at all.
The decision
A grounding contract enforced in the pipeline, not the prompt: answers may only be assembled from retrieved passages, every answer carries its citations, and when retrieval confidence falls below threshold the system refuses instead of guessing.
What it bought
Answers that can always be traced back to a source document, and a refusal path you can trigger on demand. The same contract runs live in this site's concierge — ask it something outside its corpus and watch it decline.
RAGVector searchLLM orchestrationNode.js
Test the live concierge →
CMZ portalproves · ERP and business system replacement

A high-traffic portal that stopped lying to its operators

The problem
Operators on a busy enterprise portal were acting on stale numbers between polling ticks, while the polling itself hammered the database with 'nothing changed' reads at scale.
The decision
Flip the model: push over WebSockets so the server speaks only when state actually mutates, with caching centralised at a single read-through boundary instead of scattered through controllers.
What it bought
Every client sees the same value in the same frame, a whole class of acted-on-stale-data mistakes stopped happening, and the origin database was shielded from read spikes.
WebSocketsRedisReactNode.js
The real-time architecture →
Hospital-APIproves · Architecture review & advisory

The query that got slow — and the fix that wasn't hardware

The problem
A clinical workflow API's aggregation pipeline degraded as data grew: same query, same result, vastly more work — the classic case where the instinct is to buy a bigger database.
The decision
Profile before spending: read explain('executionStats'), then reorder — filter first on indexed fields, join late against the already-small set, and design every stage around the smallest possible document flow.
What it bought
The speedup came from reordering stages against measured numbers, not from a bigger instance — exactly the kind of finding an architecture review exists to put in writing before money moves.
MongoDBExpressNode.js
The optimization, step by step →

What I will tell you that a vendor will not

  • When you should buy, not build. If an off-the-shelf tool solves eighty per cent of it for a fraction of a build, that is what the review will say. Custom software is the right answer far less often than people selling custom software suggest.
  • When the scope is too large for one engineer. Some work needs a team of twenty and a support rota. I will say so rather than take a project I cannot land, because a half-delivered system is worse for you than a firm no.
  • What it will actually cost to run. Build cost is the part everyone quotes. Hosting, model spend, and maintenance are what surprise people in year two, so they are estimated up front and in writing.
  • Where your existing quote is real. Not every enterprise proposal is padded. Sometimes the number is fair and the answer is to proceed with them — you will be told that too.

How an engagement runs

  1. 01

    A call that costs nothing

    Thirty minutes. What you are trying to fix, what you already run, and what it has been quoted at. You leave with an honest opinion on whether this is worth building at all.

  2. 02

    Written scope and a fixed price

    What will be built, what will not, the technologies, the milestones, and the number. Agreed before any work begins, and it does not move unless you change the scope.

  3. 03

    Build in the open

    Code goes into your repository from the first commit. Weekly demos of something running, not status reports. Payment is staged against delivered milestones.

  4. 04

    Handover, then step back

    Source, deployment, documentation and a training session for your team. You can maintain it yourself, hire anyone else, or keep me on. No licence, no lock-in.

Do not take any of this on trust. Go and check.

Every system below is documented with its architecture, its trade-offs, and what it cost to run. Read those before you read the pricing.

Mobile · AI Agent

Sable

A privacy-first personal finance agent that keeps 100% of your financial data on-device in SQLite — no cloud backend. An OpenAI function-calling agent tracks debts and pushes proactive briefings, with every database mutation gated behind a Review & Confirm boundary.

React Native (Expo)TypeScriptSQLiteZustand
Read the teardown →Desktop · Rust

streamerOS

A Rust-powered desktop cockpit for Twitch & YouTube streamers — live system telemetry, multi-platform chat velocity, and automated OBS scene sync, all inside a ~152 MB / 1.8% CPU footprint.

RustTauri v2WebSocketsNext.js
Read the teardown →Automation · Agent

Automated LinkedIn Pipeline

A Python autonomous agent running on GitHub Actions that schedules and publishes technical content on a cron — drafting every post through the Gemini API. Zero servers, zero manual posting.

PythonGitHub ActionsGemini APICron
Read the teardown →Pipeline · Content

Zero-Cost AI Blog Writer

A native Next.js pipeline that autonomously writes, formats, and deploys Markdown articles straight to this site — Gemini drafts the MDX, GitHub Actions commits it, and GitHub Pages ships it.

Next.jsMDXgoogle-genaiGitHub Actions
Read the teardown →
Client and enterprise work →Read the source on GitHub ↗Employment history ↗

Book the free call

Thirty minutes, no charge, no pitch. Bring the problem and any quote you are weighing up. You leave with an honest read on what it should cost and whether it is worth building at all.

or email contact@streamerosai.com