Daqeeq is a senior-only engineering company. We build AI agents, LLM pipelines and the MLOps around them, plus the web and mobile platforms they live in — and we bring the evidence: benchmark sets, regression gates and measured accuracy, not demos. The engineer you meet is the engineer who writes your code.
Building software
Avg years per engineer
Apps shipped to stores
Juniors on delivery
Trusted by teams behind
ZoomShift Fluxx RightInbox DirectSubs Ramp Ventures Space Time ConsultingWhat we lead with
Anyone can wire up a model and show a good screenshot. The hard part is making it reliable, measurable and safe to change. That is the part we do: agents with a small, auditable action surface, MCP servers your customers can plug their own AI into, the MLOps that turns a notebook into a release, and a number you can defend to your board.
Search accuracy on the client's own audit
Faster than the hosted-LLM pipeline it replaced
MCP tools live in a production helpdesk
Email to book a call with our scheduling agent
Multi-step orchestration where the logic lives in reviewable configuration, not scattered prompt strings.
Retrieval that understands your domain vocabulary instead of matching keywords and hoping.
The offer almost nobody else makes. We tell you how good your AI actually is, with a number.
When a general model is not accurate enough on your domain, we train one that is.
Agents that act inside your product with a small, auditable action surface, and MCP servers so any AI client can work your data with the permissions you set.
The pipeline around the model: data you can regenerate, training you can reproduce, serving that scales, and an eval loop that makes the ship decision.
Search, extraction, summarisation, classification and chat — shipped into software that already has users.
For regulated buyers who have to answer "why did it say that?" — every claim traceable to a source.
Recent work
Client names are withheld under NDA. The numbers are not — every figure below comes from a real audit, gate run or deployment log on live production systems.
A customer-support platform needed an agent that answers customers on its own without inventing anything, and a way for reps to work the inbox from inside Claude Desktop, Cursor or any AI assistant. We shipped a grounded support agent and a twelve-tool MCP server with permission tiers, suggest-only autonomy and bug routing to Linear, Jira and GitHub. Both live for paying customers.
MCP tools, 3 tiers
Autonomy modes
Answers outside the KB
Booking a call across Lahore and US time zones cost senior engineers four to six emails each. We built Geralt, an agent that lives in email: copy it on one message, it proposes slots, reads free-text replies, sends calendar invites and escalates to a human only when it must. No app, no login, no dashboard.
Email to book a call
Apps or logins
Runs on its own
A model in a notebook is an experiment. We built the operations around a marketplace's search models: a repeatable labelling pipeline, versioned fine-tuning runs, GPU serving with autoscaling, an LLM-as-judge evaluation loop and a regression gate that blocks bad releases before customers see them.
Median query time
Judge hit rate vs 72.4%
Fixtures in the gate
A UK life-sciences talent marketplace, operating across the UK, US and Australia, could not reliably match specialist briefs to the right people — the vocabulary of the industry defeated keyword search. We rebuilt the engine around embeddings, reranking and a domain taxonomy, then built the evaluation layer that proved it worked before anything shipped.
Exact-match accuracy
Regression fixtures
Byte-identical replay
A React Native app had never once produced a TestFlight build, and the store deadline was closing. Nine consecutive CI failures — dependency locks, stale pods, signing keys, and finally a C++ compiler error deep inside a formatting library — were each root-caused and fixed. We also rejected the expensive fix that would not have worked.
Build failures cleared
TestFlight build ever
Framework upgrades needed
A production marketing site went down to an SEO-spam compromise. We identified the entry vector — an unauthenticated API route — removed the web shells and scheduled-task persistence, restored files and database from a verified clean snapshot, rotated every credential, closed the hole and left a written incident report behind.
Diagnosed to restored
Backup tiers installed
Credentials rotated
How to start
Fixed scope and a named engineer wherever possible, so you know what you are buying and who is building it. For AI, most clients start with a pilot and grow from there.
4–6 weeks · fixed price, agreed up front
Pick one job you want AI to do: an agent, a search, a classifier, an MCP server for your product. We agree the success metric with you before we start, build it against your own data, and hand it over running, with the evaluation harness that measured it.
≈ 2 weeks · fixed fee
You have AI in production and you are not sure how much to trust it. We build a benchmark set from your own data, run it, and hand back a scored report on exactly where it fails — plus the harness so you can re-run it forever.
Best for: teams shipping AI features without a way to measure them.
Days · fixed fee
A blocked build, a dead pipeline, a store rejection, a security incident. Something is on fire and it needs someone senior today. We diagnose, fix, and write up what happened so it does not happen twice.
Best for: urgent production problems with a deadline attached.
6–8 weeks · 2–3 engineers
A named, self-directing team for a new build or a significant feature. Architecture, delivery and QA included. No coordination tax on your side and no ramp-up you pay for twice.
Best for: a real project that needs to exist in two months.
Ongoing · part or full time
One of our engineers takes ownership of a system inside your team — your standups, your repo, your release process. Long relationships are the point; several of ours have run for years.
Best for: a system that needs an owner, not a ticket-taker.
The rest of what we do
AI is where we lead, but it sits on top of a company that has been building and running production web and mobile systems since 2012. Both halves are the same engineers.
SaaS products, admin dashboards, internal tooling, customer portals, marketplaces and booking systems — front to back.
Native and cross-platform, taken all the way through review and onto the stores. Over 40 published apps between the team.
Infrastructure that can be rebuilt from scripts, deployed safely, and understood by whoever comes next.
Authentication done properly, authorisation flaws found and closed, and incident response when it has already gone wrong.
How we work
Our industry has a reputation problem. These are the specific ways we refuse to earn it.
We assign dedicated teams rather than showing you a senior engineer and then routing the work to a junior. The people you interview are named in the contract and they are the people who write your code. You can check at any time — that is the point.
We would rather do excellent work for a handful of companies than adequate work for everyone. Some of our engagements have run for years, and our clients tend to bring us their next project rather than re-tender it.
Every engineer here works AI-assisted, every day. That is why a team of this size covers this many languages and ships at this pace — and why we can be honest about what these tools do well and where they quietly fall apart.
Winning the work is easy; meeting the date and owning the production incident at 11pm is where most software houses quietly fail. We stay on after launch, take the support calls, and treat your system as ours to keep running.
Stack
Not a logo wall of everything that exists. This is the set our engineers have shipped and operated for paying clients — and because we work AI-assisted, we take on languages outside it when a project needs one.
The bench
This is the whole team — not a shortlist we show buyers. They average well over fifteen years each, they all work AI-assisted, and they are the people who will be on your calls.
Founder & CEO
Principal engineer · AI systems
CTO
Architecture · Consulting
Principal Architect
12+ years · Python, AWS, Bedrock
Senior Front-End & Mobile Engineer
17+ years · 40+ App Store apps
Principal Engineer
15 years · Full-stack veteran
Senior Software Engineer
Backend · Platform
Front-End Expert
Interfaces · Design systems
Software Engineer
Web · Product delivery
AI Content & Video
Video · Photography · AI media
In their words
Named, real, and unedited apart from length.
“Daqeeq.net (Abdullah's team) was highly recommended to me by a colleague of mine. They proved to be a very valuable contributor to Fluxx over the last year. They are very focused and driven and will go the extra mile to get the job done. Although we are separated by 12 time zones, they manage to bridge the gap. They are very easy to work with. I hope to continue to work with Abdullah and his team as long as they are available.
“Abdullah worked with us for several years directing our development on several projects. He was outstanding at architecting and building solutions for our products and bringing good developers to the team as needed. His exceptional network also helped him to source and find creative answers to complex technical issues. Abdullah brings with him a strong work ethic, technical curiosity and has unquestioned trustworthiness.
“Working with Daqeeq has been a great experience. They are quick to listen, fast to pick up new skills and truly a pleasure to work with. We've already booked them for our next contract!
“Abdullah is a highly talented Software Engineer who gets the most challenging of problems resolved once he puts his mind to it. As a mentor, he always helped junior developers and encouraged them to apply best practices in development. I wish him all the best in his career, and look forward to working with him in future.
Earlier work
A selection of platforms our engineers have delivered over the years — several of them still in production, and several of the relationships still going.
Employee scheduling platform, used by businesses including Amazon and Holiday Inn. We led its modernisation on AWS.
Email tracking and scheduling software, with users at companies including Uber, HubSpot, Netflix and Salesforce.
Cloud grants-management platform enabling data-driven grantmaking for foundations and funders.
Marketplace connecting real-estate investors with local contractors for flips, rentals, renovations and new builds.
Member platform for the Australian diamond industry, connecting dealers and colleagues nationwide.
Meeting scheduling application that finds a time for everyone without eating up a bunch of it.
Coupon and deals platform covering thousands of online stores, helping shoppers find the best price.
White-label SaaS generating free SEO reports with the data needed to improve on-page and off-page ranking.
A blocked release, an AI feature you cannot measure, a system nobody owns, or a product that needs building from nothing. Send us the real version — you will get a senior engineer on the reply, not a sales script.
Find us
Building No. 60-S, 2nd Floor, Commercial Imperial Garden Block,
Barki Road, Paragon City, Lahore 53200, Pakistan
Monday – Friday, 9am – 6pm PKT
We overlap US time zones on request.
Tell us about the project or the problem. We reply to everything, usually within one working day.
