Services
AI & data
The hard part of AI is rarely the model. It is evaluation, cost, latency, and what happens when the output is wrong. LebSource builds AI and data work that survives real users, and says plainly when a much simpler approach would do the job better.
01
Outsourcing AI & data: why it goes wrong elsewhere
AI is the easiest thing in software to demo and the hardest to keep working. A prototype that impresses in a meeting can be wrong a quarter of the time, cost more per request than the feature earns, and have no way to tell you it has degraded. The firms worth hiring are the ones that measure those three things before quoting, and the ones willing to tell you the answer is a search index.
The comparison
AI & data vs an agency vs a far-shore partner
The three realistic ways to get this built, compared on the things that decide whether it lands.
Before anything is built
A local agency
A proposal for the AI project you asked about.
A far-shore build partner
A quote against your specification, as written.
LebSource
A feasibility assessment: realistic accuracy, cost per request at your volume, and a plain answer if AI is the wrong tool.
How quality is judged
A local agency
Demos and spot-checks against examples chosen to work.
A far-shore build partner
Acceptance against the written spec, which rarely defines what “correct” means for a model.
LebSource
An evaluation set that runs on every change, like a test suite. Regressions show up as failures, not as complaints.
When the model is wrong
A local agency
Handled as a defect after users report it.
A far-shore build partner
Out of scope unless the specification anticipated it.
LebSource
Designed for up front: answers grounded in your data, outputs constrained to a structure, failure handled explicitly.
Running cost
A local agency
Frequently discovered in the first full month of production.
A far-shore build partner
Not usually the build partner's problem.
LebSource
Measured at assessment and engineered against. Cost and latency are acceptance criteria, not surprises.
Where your data goes
A local agency
Covered by a standard data-processing addendum.
A far-shore build partner
Wherever the chosen provider defaults to.
LebSource
Data handling and residency agreed in writing before build starts, including which providers you will accept.
“Far-shore” here means a delivery team six or more hours from your working day. That is a statement about time zones, not about anyone’s ability, plenty of excellent teams work that way, and for well-scoped, low-iteration work it can be the right call. The comparison describes delivery models, not any particular firm.
How we work
What we put in writing
Every firm claims quality. These are the commitments specific enough that you would notice us breaking them.
We tell you when you don't need us
If a cheaper tool, a simpler approach, or no project at all is the right answer, you hear it at the scoping stage, before you have paid for a build. We would rather lose the engagement than deliver the wrong thing well.
Stop after any stage, keep everything
Work is sequenced so each stage stands on its own and is verifiable before the next begins. There is no point in the engagement where stopping leaves you with nothing usable.
You own it from day one
The code, the infrastructure, and the documentation are yours throughout, not handed over at the end, and not held as leverage. Taking the work in-house later is a planned handover, not a negotiation.
Your working day, not a handoff
Beirut runs on EET/EEST and shifts with the same daylight-saving changes as Europe. Questions get answered inside your day, so a blocker costs you an hour rather than a night.
Nothing we build fails silently
Everything ships with error handling, alerting, and a named owner. Software that breaks quietly is worse than the manual process it replaced, and we treat it that way.
Senior people, at up to 43% less
The saving comes from where the team sits, not from staffing your project with juniors and calling them consultants. The people scoping the work are the people doing it.
Scope
What our AI & data services cover
Feasibility before build
A short assessment of whether the problem suits AI at all, what accuracy is realistic, and what it will cost per request at your volume.
AI features in production
Retrieval over your own data, structured outputs, explicit failure handling, and an evaluation set that runs like a test suite instead of vibes.
Data pipelines and warehouse
Ingestion, modelling, and orchestration so the numbers behind your reporting are current and reconcilable.
Reporting people trust
Dashboards built on documented metric definitions, so the same question gives the same answer next quarter.
Process
How our AI & data process works
Step 01
Assess
Is this an AI problem, and what is realistic at your volume and budget?
Step 02
Prototype
A narrow version, measured against a real evaluation set.
Step 03
Productionise
Cost, latency, failure handling, and monitoring.
Step 04
Operate
Ongoing evaluation as your data and usage change.
Fit
Who our AI & data team is right for
Deliverables
What you get from an AI & data engagement
Every item below is something handed over and owned by you at the end, not a description of activity.
A feasibility assessment stating realistic accuracy, cost per request at your volume, and whether AI is the right tool at all.
An evaluation set that runs on every change, so quality regressions surface as failures rather than complaints.
The AI feature in production, with retrieval over your data, structured outputs, and explicit failure handling.
Data pipelines and models behind the reporting, documented and reconcilable.
Dashboards built on written metric definitions, so the same question returns the same answer next quarter.
Cost and latency monitoring, with alerting on both.
The stack
Tools and platforms we build AI & data on
What we work in day to day. If your environment is not listed, it is worth asking rather than assuming.
Models and serving
- OpenAI and Anthropic APIs
- Open-weight models where they fit
- Vector search and retrieval
- Structured output and function calling
Data
- Python and SQL
- dbt
- Airflow and Dagster
- Snowflake, BigQuery, PostgreSQL
Evaluation
- Automated eval suites
- Regression tracking per change
- Cost and latency budgets
Reporting
- Metabase and Looker
- Power BI
- Documented metric layers
We work in your stack rather than moving you onto ours. Where we think a choice is wrong we will say so and explain why, then build what you decide.
Engagement
How to buy an AI & data project
Three shapes, and we will tell you which one fits before you ask. The wrong shape is a more common cause of failure than the wrong team.
Fixed scope
An agreed deliverable, an agreed price, an agreed date. Works when the thing being built is genuinely well understood, which is rarer than most proposals pretend.
Best for
A defined build with stable requirements
Retained team
A team held for you monthly, working through a priority list you control. Scope moves as you learn without renegotiating a contract every time it does.
Best for
Ongoing work where priorities shift
Discovery first
A short paid piece that ends in a written scope, an architecture, and a real estimate. If the answer is that you should not build it, you get that in writing and owe nothing further.
Best for
An idea that is not yet a specification
Elsewhere
Other outsourcing services from LebSource
Every one is delivered the same way: scoped in writing, run by our team, shipped in your time zone.
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FAQ
AI & data with LebSource
Will you tell us if AI is the wrong answer?
Yes. A rules engine or a better search index is often cheaper, faster, and more predictable, and we would rather say so at the assessment stage than build the wrong thing well.
How do you stop AI features producing nonsense?
Grounding answers in your own data, constraining outputs to a structure, handling failure explicitly, and running an evaluation set on every change.
Where does our data go?
We agree the data handling and residency model in writing before any build starts, including which providers are acceptable to you.
Next step
Ready to build or scale your team?
Tell us what you need and we will match you with pre-vetted Lebanese professionals ready to integrate with your team.