AI agent development that ends in production, not demos.
We build Claude, MCP, RAG and voice agents for Next.js and Python SaaS from a short written plan you approve, then ship in increments you review. 2,000+ hours on AI products, rated 5.0 on Upwork.
Agents, Claude and MCP, RAG, voice, AI features for an existing SaaS, MVP rescue and full AI SaaS builds. Every one starts with a written plan from $2,500 and ships in increments you review.
LLM features inside the product you already run, in your codebase, with costs you can predict.
AI writing assistant
Saved
Release notes
This update makes exporting faster and easier to find.
The export button, which was previously located in the settings menu under the advanced section, has now been moved so that it is in the toolbar.The export button, which was previously located in the settings menu under the advanced section, has now been moved so that it is in the toolbar.Export now sits in the toolbar instead of advanced settings.
RewriteShorter
+Export now sits in the toolbar instead of advanced settings.
1,145 hours over six months on an enterprise knowledge platform. Around 800 hours on an agent platform with real-time voice. 162 hours on an in-editor writing assistant. Each rated 5.0 by the client on Upwork.
Autonomous multi-agent workflows with real-time voice, built over around 800 hours and rated 5.0.
AI writing assistant
Saved
Release notes
This update makes exporting faster and easier to find.
The export button, which was previously located in the settings menu under the advanced section, has now been moved so that it is in the toolbar.The export button, which was previously located in the settings menu under the advanced section, has now been moved so that it is in the toolbar.Export now sits in the toolbar instead of advanced settings.
RewriteShorter
+Export now sits in the toolbar instead of advanced settings.
A live music ticketing platform gained AI agents, an MCP server and automated reporting, from one full-stack team.
A written plan first, then software you review as we go.
You see the plan before the invoice and the software before the launch. Nothing waits for a big reveal.
01
Plan
A short written document: architecture, edge cases, trade-offs and what to ship first. You agree it before we build, and you can take it to any team.
02
Build in small increments
Working software in pieces you can click through, each with a written update. Feedback lands while it is cheap to act on.
03
Ship
Deployed to production with tests, monitoring and documentation your team can follow without us in the room.
04
Support
We stay on to fix, tune and extend, or hand the codebase over cleanly. Either way it sits in repositories you control.
What clients wrote, word for word
Four reviews from the Upwork work history, quoted verbatim with the contract each one came from. The rest of the featured contracts closed at 5.0 without a written comment.
5 out of 5
“Always happy working with Ahmad. He is considered a "team member" in my business.”
Client, 70-page marketing websiteWebsite build to a provided template, 2022
5 out of 5
“He is very talented and can solve so many issues. A trusted and loyal worker.”
Client, Shopify storeShopify webshop with 50+ products, 2022 to 2023
5 out of 5
“Always been very satisfied with Ahmeds work. He is very versatile and can solve many different tasks.”
Client, long-running web retainerSite administration and fixes, 2021 to 2023
Senior TypeScript full-stack developer with LangGraph2025 to 20265 out of 5
Full-stack JavaScript developer for an AI-integrated app20255 out of 5
First-in-class editor in Next.js on TipTap2023 to 20245 out of 5
Python and Next.js migration from MongoDB to MySQL20235 out of 5
Not ready to talk? Take the checklist.
Fifteen checks we run before real users and real data hit an AI product: prompt caching, context budgets, approval steps, row-level security, agent state, traces. We email you the link.
What would you build?
Pick the one closest to yours. You get the architecture we would start from, the stack it runs on, the order of work and the nearest project we have shipped.
Most tickets ask questions your help docs already answer, and the support team spends the day finding and pasting the same replies.
An agent reads each ticket, retrieves the matching help articles and drafts a reply with its sources attached. A support rep approves or edits the draft before it goes out, and the approval log shows which ticket types the agent can later handle on its own.
Illustrative architecture. Yours comes out of the written plan, after we have seen your systems and data.
The answers your team needs are spread across PDFs, decks and wiki pages, and finding one means asking whoever remembers where it is.
Documents convert in the background, get chunked and indexed, and an agent answers questions with the source passages shown beside each answer. When the agent proposes an edit to the knowledge base, an editor approves it before anything is written back.
Illustrative architecture. Yours comes out of the written plan, after we have seen your systems and data.
Calls come in all day with the same questions and booking requests, and whoever picks up has to stop what they were doing.
A real-time voice pipeline turns speech to text, an agent decides what to do, and a synthesized voice replies inside the conversation. Bookings and lookups run through structured tool calls you define, and anything outside those tools is handed to a person on the call.
Illustrative architecture. Yours comes out of the written plan, after we have seen your systems and data.
The prototype won your first customers, and now it breaks on real data, has no tests, and every fix risks breaking something else.
We audit the code and write a keep, fix or rebuild plan you approve before any build work starts. Then we fix the foundations in small increments while the product keeps running: auth and row-level security, a multi-tenant data model, background jobs, a cached and budgeted AI layer, tests and CI.
Illustrative architecture. Yours comes out of the written plan, after we have seen your systems and data.
Working with a studio in Lahore
The questions every remote client asks us, answered here so the call can be about your product.
You're nine hours ahead of us. How does that work?
Lahore is UTC+5: four hours ahead of Berlin, nine or ten ahead of New York. We keep our afternoons and early evenings open for calls, which covers the whole European working day and US East Coast mornings. The plan and every increment review are written, so you can read them over coffee and reply when it suits you.
How often will we hear from you, and where?
A written update with every increment, calls at the cadence you choose, and replies to messages within one working day. We work inside your tools: your chat, your issue tracker, your repository. There is no separate client portal to log into.
Who owns the code and the IP? Will you sign our NDA?
You do. Code, designs and documentation we write for your project are assigned to you on payment; the clause is in our standard agreement. Yes to the NDA: send yours and we sign it before you share anything about the project.
Where does the code live?
In repositories you own, from the first commit. We work on branches and open pull requests you can read. If we ever part ways, you have everything, including the written plan and the handover notes, and no access of ours is needed to deploy.
Who actually writes the code?
Senior engineers who plan and build the work themselves. The person on your architecture call is the person who writes the plan and then the code. We do not hand work to a junior bench, and nothing is subcontracted without telling you.
What happens in week one?
Day one is a kickoff and access setup. Days two and three go into the written plan: architecture, edge cases, trade-offs and what to ship first. You review it on days four and five, we adjust it together, and the first increment is scoped before the week is out.
What if the scope changes halfway through?
It usually does, a little. Changes are written down, estimated and agreed before anyone builds them, so the invoice never surprises you. Fixed-scope builds are priced against the written plan; if the plan changes, the price changes with it, in writing.
Why not hire a freelancer from a marketplace?
We came up through Upwork, so we understand the appeal. The difference is the written plan before the build, increments you review rather than a final reveal, and one team that covers the AI layer, the full-stack product and the deployment. Our Upwork record is public if you want to check it.
Your first week
Day 1
Kickoff and access
A call to walk through your product, your data and your constraints. You grant repository and tool access; we agree the overlap hours and where updates land.
Days 2–3
The written plan, drafted
Architecture, edge cases, trade-offs and what to ship first, written as a document you can forward to anyone on your team.
Days 4–5
Plan review and first increment scoped
We go through the plan together, change what needs changing and agree the first increment, with its scope and review date written down.
Start with the plan. The build is priced against it.
A discovery sprint from $2,500 produces the written plan. A fixed-scope build from $6,000 is priced against that plan. A monthly team from $45/hr keeps a product that is already live moving.
Discovery sprint
From $2,500
A short, fixed engagement that turns your idea, prototype or codebase into the written plan, the document every build is priced against. Yours to build from, with anyone.
What's included
Review of your idea, prototype or existing code
Architecture, edge cases and trade-offs in writing
A recommended first release, and what to leave out
Scope and estimate for the build
Timeline
Short and fixed, agreed before we start.
Best for
Teams with a clear problem and an unclear path to production.
A written plan you approve before any build money changes hands
Small increments you review as we go; scope changes agreed in writing
Code in repositories you control from the first commit
Starting prices in USD. Every quote follows a written plan, so you see the scope before you commit.
Questions teams ask before they book.
Anything not covered here, ask on the free architecture call or email info@tecifo.com.
About Tecifo
Tecifo Solutions is an AI agent development company in Lahore, Pakistan. We build Claude API and Claude Code apps, MCP servers, RAG, LLM integrations and AI voice agents in Next.js and Python SaaS, and we take Lovable and Bolt MVPs to production. The team holds the Certified Large Language Model Developer (CLLMD) certificate.
The record is public: Top Rated Plus on Upwork, $100K+ earned across 22 jobs, five stars on every featured contract, identity verified. Every project starts with a short written plan and ships in small increments you review.
Free 30-minute call. You leave with a written summary of the approach and a sensible first step. Prefer writing? Send a brief and we reply by email with questions.
