AI Development
Applied AI in real products
LLM features, agents, and automation that survive contact with real users and real budgets.
Start a projectAI Development
Why choose ai development services
Shipping AI means evaluation suites, failure modes, cost controls, and rollback paths. We integrate models into your product with the same rigor we apply to payments or auth: observable, testable, and safe to iterate.
01
Production-first AI integration
LLM features wired into your product with logging, cost controls, and fallbacks.
02
Evaluation before scale
Golden datasets and automated checks before full rollout to real users.
03
RAG and agent workflows
Retrieval, tool use, and human-in-the-loop paths for high-risk outputs.
04
Multi-provider routing
OpenAI, Anthropic, and open models selected by task, latency, and cost.
05
Guardrails and monitoring
Schema validation, moderation hooks, and regression checks on model changes.
06
Trusted AI engineering partner
We ship AI that survives production traffic, not demos that break under load.
Outcomes
Key benefits of ai development services
Product teams adding LLM features, automation, or retrieval systems who need production guardrails, not a demo that breaks under real load.
- AI features you can ship, measure, and roll back
- Documented failure modes before users hit them
- Economics that scale with usage, not surprise invoices
Tech stack
Built with the right technologies to deliver scalable solutions
- OpenAI
- LangChain
- Anthropic
- Python
- TensorFlow
- Hugging Face
- n8n
Testimonials
What partners say about working with us
Client quotes from recent engagements.
“Stacklance is an exceptionally sharp and thoughtful engineering partner. What sets them apart is their dedication to the project's long-term success: they don't just write code, they look out for our best interest. Their meticulous, measure-twice approach takes a bit more time upfront, but the result is high-quality, bug-free architecture. If you want a team that truly gets the business logic and won't cut corners, I highly recommend them.”
“The best engineering partner we've worked with. Amazing work, high quality, extremely fast delivery, and great communication throughout. They shipped our MVP on schedule and left the codebase in a state our team could extend without friction.”
“Stacklance brought strong platform expertise to a project with difficult constraints. They went above and beyond on solutions, followed our guidelines closely, and got creative when the easy path wasn't available. I would definitely work with Stacklance again.”
“They were patient and took the time to explain our scaling issue before resolving it. They also put protocols in place to help prevent future occurrences. Clear communication and solid follow-through after delivery.”
“An excellent engineering resource. Stacklance ensures requirements are understood, communicates often on progress, completes work to spec, and follows up with great support after delivery. Would recommend to anyone building a production web product.”
“Stacklance helped us ship AI features without breaking production. Evals, guardrails, and a clean rollout plan were part of the delivery, not an afterthought. Highly recommended for teams adding LLM workflows to existing products.”
Process
Our process
How we move from discovery to launch with visible checkpoints at every stage.
01
Use case and risk mapping
Success metrics, failure modes, data handling, and compliance constraints.
02
Prototype and evaluate
Small experiments with golden datasets before full integration.
03
Architecture and design
APIs, queues, caching, and fallback paths planned for production load.
04
AI feature development
Models, prompts, retrieval, and tools wired into your application.
05
Integration and testing
Eval suites, load checks, cost monitoring, and moderation hooks.
06
Deployment and launch
Feature flags, staged rollout, and logging for safe production release.
07
Monitor and iterate
Regression checks and model upgrades without quality drift.
Deliverables
What we ship
- LLM integration and prompt/workflow design
- RAG pipelines and knowledge retrieval
- Evaluation suites and regression checks
- Guardrails, moderation, and audit logging
- Cost monitoring and model routing
Use cases
Common projects we take on
Representative work types under this practice. Your brief may combine several.
- Copilots and assistants inside existing products
- Document Q&A and internal knowledge search (RAG)
- Workflow automation with human-in-the-loop approval
- Classification, extraction, and summarization pipelines
- Evaluation and monitoring for model upgrades
Scope
What is in and out
Included
- LLM integration and workflow design
- Evaluation datasets and automated checks
- Guardrails, logging, and moderation hooks
- Cost and latency monitoring dashboards
Not included by default
- Training custom foundation models from scratch
- Legal review of data processing agreements
- Unbounded prompt tuning without evaluation criteria
Engagements
Ways to work together
Flexible models depending on stage, runway, and internal team capacity.
- AI feature module (fixed scope)
- RAG or agent pipeline build
- AI reliability audit and hardening
Industries
Tailored solutions for diverse industries
- SaaS & Startups
- EdTech
- HealthTech
- Real Estate
- LegalTech
FAQ
Frequently asked questions
Common questions about ai development before we scope an engagement.
Ready to scope ai development?
Share a brief on the contact page. We typically reply within 24 to 48 hours.