I’m Wasim Ranjha, your Python & AI developer. I help businesses automate repetitive work, handle customer calls, and turn product ideas into working software.
Phone agents, chat assistants, and search tools connected to your documents and business software.
Python / FastAPI / RAG
Give routine calls, questions, and document searches a better workflow.
I build voice agents, chat assistants, and search tools connected to your business data. We start with one specific task and decide where a person should stay in control.
What’s included
Voice or chat workflows matched to your business
Answers grounded in your documents and knowledge base
Connections to the tools your team already uses
Testing, deployment, and a documented handover
Where we’ll start
Which questions or tasks come up most often?
What information can the assistant access?
When should the assistant hand over to a person?
02
Web apps & SaaS
Customer portals, internal tools, and SaaS products. Frontend, backend, and deployment handled together.
React / Python / Django
Build the product your customers and team actually need.
I work on both sides of a web application: the interface people use and the backend that keeps it running. That can mean a first release, an internal portal, or extending an existing product.
What’s included
A responsive interface built around your main workflows
Django or FastAPI backend and database design
Authentication, roles, and the integrations in your scope
Deployment and documentation for your team
Where we’ll start
Who will use the application?
What must the first release let them do?
Are we building from scratch or working with existing code?
03
Web scraping & data pipelines
Collect and clean the information you need, then deliver it to your database or team.
Python / Playwright / Selenium
Get useful data without repeating the same research every day.
I build extraction and monitoring tools that collect data from agreed sources, clean it, and deliver it in a format your team can use. The approach depends on the source, update frequency, and access requirements.
What’s included
Extraction scripts for the sources in your scope
Data cleaning and structured exports
Scheduled collection and monitoring where needed
Error handling, deployment, and operating instructions
Where we’ll start
Which sources and fields do you need?
How often should the data update?
Where should the results go?
04
Cloud deployment & DevOps
Set up the infrastructure, databases, and deployment process around your application.
AWS / DigitalOcean / Docker
Take your application from a local build to a maintained deployment.
I help configure the infrastructure around your application, including databases, containers, deployment pipelines, and API access. We review the existing setup before choosing what to change.
What’s included
A deployment plan for your application
Cloud and database configuration
Build and deployment automation
Handover notes and an agreed support scope
Where we’ll start
Where does the application run today?
What reliability or scaling problems are you seeing?
Who will operate it after handover?
05
Mobile app development
iOS and Android development with my specialist team, supported by the APIs I build.
Flutter / React Native / Mobile UI
Put your product in your customers’ hands.
For mobile projects, I coordinate with my specialist team on the application and work on the backend and integrations it needs. We choose the platform and release scope around your users.
What’s included
A defined iOS or Android release scope
Mobile screens and core user flows
Backend APIs and integrations
Testing and release preparation
Where we’ll start
Do you need Android, iOS, or both?
Which device features does the app need?
Is there an existing backend or design?
06
Design & visual content
Interface design, brand assets, and video production with my creative team.
UI design / Brand identity / Graphics
Give your product a clear, consistent visual identity.
I collaborate with a specialist creative team on interface design, brand assets, and AI-assisted video work. We agree on the deliverables and visual direction before production.
What’s included
A visual direction based on your brief
Interface, brand, or video assets within the agreed scope
Review rounds and refinements
Final files in the formats you need
Where we’ll start
What are you making, and who is it for?
Do you have existing brand guidelines?
Which formats and deliverables do you need?
03 / ABOUT ME
Wasim Ranjha. Your development partner.
Also known as Waseem Ranjha · Python & AI full-stack developer
I’ve spent the last five years working with Python, web applications, and more recently, AI systems. I enjoy taking a messy process and turning it into something people can use without thinking twice.
My work covers Django and FastAPI backends, React interfaces, voice agents, and cloud deployments. You’ll work directly with me on the technical decisions and progress.
SaaS platforms, voice agents, FastAPI backends, and AWS deployments.
2022 — 2024
Backend Python Developer
Tiksom Limited
Django APIs and React features for applications across multiple industries.
2021 — 2022
Python Developer
NeXskill
Hands-on application development with Django and Flask.
Education & professional training
ICS — Computer Science, Degree College Kot Momin (2018–2020). Professional training and mentorship in Python and backend systems at NeXskill.
04 / WORKING TOGETHER
From the first call to the final handover.
We agree on the scope first, then work in small, reviewable steps.
01Discover
Start with the problem
Tell me what you need, who will use it, and what isn’t working today.
02Design
Agree on the scope
Agree on a focused scope, architecture, milestones, and estimate before development begins.
03Build
See the progress
I share working versions for you to review, so we can catch issues and adjust early.
04Launch
Test and launch
Test, deploy, and hand over your product with documentation and an agreed support plan.
05 / CLIENT FEEDBACK
Good work starts with good people.
A few words from the people I’ve worked with.
Wasim and his team delivered our custom AI RAG platform ahead of schedule. Their deep expertise in Python, FastAPI, and AWS deployments saved us months of engineering effort and provided a robust, highly scalable system.
Ronald BensonCEO at Spector · USA
01 / 04
06 / RATES
Choose a starting point.
These are my hourly rates. I’ll estimate the work once we’ve discussed your requirements.
Notes on the decisions behind the code. Open a topic to read more.
01Document searchSearching documents with FastAPI and pgvectorHow a document becomes a useful, traceable answer.
Engineering notes · Wasim Ranjha
Start with the source
A useful document search tool needs more than an upload button. It needs to keep track of where each passage came from, who may read it, and whether the source has changed. I would settle those requirements before choosing a model.
Build retrieval first
A practical starting point is to split documents into passages, store their embeddings alongside source references, and retrieve relevant passages for each question. pgvector adds vector similarity search to PostgreSQL, so the content and its metadata can live together.
Make answers inspectable
Show the source passages with the answer and let the user open the original document. Test with real questions, including questions the documents cannot answer. The useful result is an answer someone can check—not simply fluent text.
02AI workflowsCoordinating several AI agentsDecide what each step owns before adding more agents.
Engineering notes · Wasim Ranjha
One workflow before many agents
I would begin by writing down the job in ordinary steps: collect information, check it, prepare a result, and request approval if needed. If a single workflow can do that reliably, adding several agents may only make it harder to debug.
Give each step a contract
For a multi-agent design, define the input and expected output of each step. Keep shared state explicit, record failures, and put limits on retries and execution time. A task should not continue indefinitely because two agents disagree.
Keep consequential actions reviewable
Drafting a response and sending it are different actions. Separate suggestions from changes to external systems, and decide which actions need human review. Start testing with recorded examples before allowing the system to operate on live work.
03Browser automationChoosing between Playwright and SeleniumChoose around the application and team you have.
Engineering notes · Wasim Ranjha
Look at the existing setup
The starting point is the team’s language, browser requirements, and existing automation. A working Selenium suite can be worth extending. For a new project, I would compare a small end-to-end flow in each candidate rather than choose from a feature list alone.
Use meaningful selectors
Playwright’s locators support finding elements by role, label, and other user-facing properties. These are useful when the goal is to interact with the application as a person would. Selectors based only on a long chain of page containers tend to be harder to maintain.
Plan for change
Authentication, slow pages, and layout changes are part of the work. Keep test data separate, capture useful failure information, and make retry behavior deliberate. A script that succeeds once is the beginning, not the finished automation.
04LLM developmentFine-tuning or prompt engineering?Identify what is failing before choosing how to fix it.
Engineering notes · Wasim Ranjha
Name the problem
An assistant might be missing information, using the wrong format, or making the wrong decision. Those are different problems. I would collect representative examples and define what a good response looks like before changing the system.
Try the smallest useful change
For missing business information, a retrieval step may be worth evaluating. For an inconsistent format, clearer instructions and output validation may be enough. Fine-tuning is a candidate to investigate when a repeatable behavior remains difficult to achieve and suitable training examples are available.
Compare against a baseline
Keep a separate evaluation set and compare quality, cost, and response time. Include difficult and ambiguous cases. The decision should come from those results, with a clear plan for maintaining the chosen approach as requirements change.
05Voice agentsBuilding a multi-industry AI receptionistConnect business signup, phone setup, and incoming calls.
Engineering notes · Wasim Ranjha
Define the call boundaries
Kira supports medical and dental clinics, real estate, plumbing, HVAC, and other business niches. Businesses register an account, get a phone number, and connect an AI assistant to handle incoming calls using Twilio and Vapi. The wider design question is where an automated receptionist should help and where a staff member should take over.
Treat booking as a transaction
For an appointment workflow, I would define how availability is checked, how details are confirmed, and what happens when a booking system is unavailable. The agent should not say an appointment is booked until the connected system confirms it.
Design the handoff
A useful handoff gives staff the caller’s request and the information already collected, within the agreed privacy requirements. Test interrupted speech, corrections, and unsuccessful calls as carefully as the happy path.
06Data pipelinesRunning Python scrapers at scaleReliable collection starts with limits, validation, and recovery.
Engineering notes · Wasim Ranjha
Agree on the data contract
List the sources, fields, update frequency, and delivery format. Decide how to represent missing values and duplicate records. These choices determine whether the collected data is useful to the team receiving it.
Control the request rate
Request pacing should account for the source and its access requirements. Scrapy’s AutoThrottle adjusts download delays using latency and a target concurrency setting, within configured limits. Whatever framework is used, errors should lead to bounded retries rather than an unlimited request loop.
Watch the output, not just the jobs
A completed job can still contain incomplete or unexpected data. Validate required fields, monitor record counts, and keep enough source context to investigate changes. Save progress so a failure does not require starting every collection again.
AI voice and chat agents, RAG systems, SaaS products, internal tools, scraping pipelines, and cloud infrastructure. My specialist team also supports mobile development and creative work.
Can you work with our existing tools?
Yes. We start by reviewing your current software and available APIs, then scope the connections your workflow needs. Integration requirements are agreed before development.
How much will my project cost?
Published hourly rates start at $15 for automation, $19 for SaaS development, and $49 for enterprise AI work. The final scope, estimate, timeline, and support are agreed together before kickoff.
What happens after launch?
Handover and support are part of the conversation from the start. The published packages include one, three, or six months of technical support depending on the engagement.
Can we start small?
Absolutely. Bring one process, one product idea, or one technical problem. We can define a focused first release and build on it as your needs become clearer.
CONTACT
Have a project in mind?
Send me a short description of what you need, even if you haven’t worked out all the details. Email and WhatsApp both work.
What happens next?
I review your goals and ask any missing questions.