Services
Engineering from
idea to production.
Every engagement ships real, working software - not slides and handoffs. We cover AI, full-stack, data, and strategy under one senior team.
190+
projects
12+yr
experience
1
senior team
Artificial Intelligence
Production AI systems built from the ground up - not PoCs, not pilots, not wrappers. Real models, real infrastructure, real delivery.
Agentic AI Development
Autonomous agents & multi-agent workflows that reason and act end-to-end.
Generative AI Development
Production GenAI - copilots, content engines, creative tools with evals and guardrails.
LLM Integration Services
Any LLM wired into your product with auth, caching, fallback, and resource management.
RAG Development
Ground LLM outputs in your private data - accurate, auditable, fast.
AI Agent Development
Autonomous workflow automation: browse, write, execute, coordinate.
NLP Development
Classification, extraction, semantic search - fine-tuned for your domain.
Software & Data
The engineering layer underneath the AI. We build the custom software, data pipelines, and cloud infrastructure that make AI systems possible.
Custom Software Development
Full-stack AI-powered product engineering, owned by you from day one.
Data Engineering & AI
Pipelines, warehouses, and feature stores that power model training and inference.
Computer Vision Development
Image recognition, video analytics, and object detection at production scale.
MLOps Consulting
Model monitoring, drift detection, retraining pipelines, and serving infrastructure.
Cloud & DevOps
AWS, GCP, Azure - CI/CD, containers, and infrastructure that deploys reliably.
Mobile App Development
AI-powered iOS and Android apps, engineered for performance and retention.
Strategy & Advisory
Senior technical judgment before you commit to an AI investment. We help you scope it right, choose the right stack, and avoid expensive mistakes.
AI Transformation Consulting
Moving AI pilots into production at scale - roadmap, change management, and delivery.
AI Product Strategy
Architecture decisions, build vs. buy analysis, and fractional CTO-level input.
Technical Due Diligence
Codebase and AI architecture reviews for investors and acquirers.
AI Training for Teams
Hands-on workshops that give your team the vocabulary and tools to work with AI.
How it starts
From first message
to shipped software
in under 3 weeks.
We don't run a lengthy sales process. A 30-minute call, a scoped proposal within 48 hours, and a kickoff within a week. Working software in your hands before the month is out.
Scoping call
30 minutes. We understand the problem, ask the hard questions, and tell you honestly if we're the right team.
Proposal in 48h
Clear scope, timeline, team composition, and approach - before you commit to anything.
Sprint kickoff
First sprint starts within 1–2 weeks. You see working software within 10 days.
Ship & hand off
Production deployment, documentation, and a post-handoff support window.
Our commitments
What you can hold
us accountable to.
These aren't aspirational values. They're the specific things clients have cited when explaining why they came back, or why they didn't need to look elsewhere.
You own the code from day one
No source-code escrow, no lock-in, no proprietary framework. Your repository, your infrastructure, full IP transfer on completion.
Senior engineers, start to finish
The engineer on your discovery call builds your system. We never swap in juniors or offshore the implementation after kickoff.
Fixed scope or clear exit clauses
Sprint engagements have fixed scope. Dedicated Team engagements include 30-day exit clauses, not 12-month minimums.
We say no when we should
If we're not the right fit - wrong stack, wrong stage, or wrong problem - we'll tell you. And we'll suggest who might be.
Senior Engineering Judgment
When we review your requirements, we push back on over-engineering and suggest faster paths. This isn't about being difficult - it's about delivering the right solution efficiently.
Client-reported outcomes
Numbers from real
production systems.
67% efficiency improvement
Replacing a manual document review workflow with a custom NLP pipeline improved per-document processing efficiency by two-thirds and reduced turnaround time from 3 days to 4 hours.
3× faster delivery
Rebuilding a legacy data pipeline on a modern event-driven architecture tripled feature deployment frequency and eliminated the weekly 'data freeze' window entirely.
Zero production incidents
A full MLOps overhaul - including drift detection, canary rollouts, and automated rollback - produced zero critical production incidents in the 12 months following handoff.
Your team
How we staff
your project.
You are part of the team. Every engagement includes your stakeholders in the process - not as spectators, but as collaborators with a seat at the table.
Engagement Lead
Project health, communication, timeline, and risk escalation
Full engagementAI Architect
System design, model selection, infrastructure decisions, and code review
Full engagementSenior Engineers (2–3)
All implementation: AI, backend, data pipelines, and frontend as needed
Full sprintsQA & DevOps
Automated testing, CI/CD, deployment pipelines, and monitoring setup
Sprints 2 onwardYour team members
Domain expertise, product feedback, acceptance testing, and handoff ownership
Weekly - you're in the loop alwaysWhat other agencies won't tell you
Uncomfortable truths
about AI projects.
Most AI projects fail because of data, not models.
GPT-4 cannot fix bad labelling, incomplete records, or features that don't exist in your database. Before we write a line of model code, we audit your data. Every time.
Fine-tuning is rarely the right first step.
Fine-tuning is brittle and often unnecessary. Prompt engineering and RAG solve 80% of use cases faster and more efficiently. We'll tell you which one you actually need.
LLM usage will surprise you without architecture discipline.
A product that looks free to prototype can require significant resources at modest scale. Caching strategy, context window management, and model tiering need to be designed in from the start.
Agents are harder than demos make them look.
A 5-minute demo of an AI agent looks like magic. A production agent handling real edge cases, recovering from failures, and operating inside trust boundaries is a serious engineering project.
Ready to start a project? Get in touch for a custom proposal.
Contact usFAQ
Questions about working with us.
What AI development services does StartxLabs offer?
We offer agentic AI development, generative AI development, LLM integration, RAG development, NLP, computer vision, custom software, data engineering, MLOps, cloud/DevOps, mobile apps, and AI strategy consulting.
How quickly can StartxLabs start a project?
After scoping and proposal, most engagements kick off within 1–2 weeks. You see working software within the first 10 days of a sprint.
Do you work with startups or only enterprises?
Both. We work with startups and enterprises across various stages. Sprint engagements are designed for teams that need fast AI validation.
What happens after the project is delivered?
Every engagement includes a post-handoff support window. You retain full ownership of the codebase with no lock-in. Many clients transition to an ongoing Advisory or Dedicated Team retainer.
Can StartxLabs integrate AI into our existing product?
Yes. LLM integration, RAG, and AI agent development are specifically designed for teams that want to embed AI into an existing product or codebase, not rebuild from scratch.
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