AI Features That Work in Production. Not Just in Demos.
We build LLM integrations and ML pipelines that hold up under real load, with evaluation frameworks, cost controls, and fallback handling engineered in from day one.
- Working proof-of-concept delivered in the first two weeks. Validate before you commit.
- Every LLM integration includes evaluation frameworks, cost controls, and fallback handling.
- All models, pipelines, and IP transferred to you at completion. No vendor lock-in.
Clients include
Track Record
Clutch Review
4.8 on Clutch · Jay Joshi, Exar North
“Integrated our systems with AI faster than we thought possible.”
Start With a Free Scoping Call
Tell us about your project. We respond same business day.
Everything Included. No Hidden Extras.
One engagement, full-stack execution. We own the outcome, not just the deliverables.
LLM Integration
GPT-4, Claude, Gemini, Llama: we build production-grade LLM features with proper caching, rate limiting, and fallback strategies so your AI works reliably at scale.
RAG and Knowledge Bases
Retrieval-Augmented Generation systems that let your AI answer questions accurately from your own documents, databases, and proprietary data.
Custom ML Models
Classification, recommendation, anomaly detection, and forecasting models trained on your data and optimised for your specific use case.
AI Product Strategy
We help you identify which AI use cases will move the needle for your business before writing a line of code. Most teams start with the wrong problem.
Sometimes we'll tell you not to build.
If AI isn't the right answer for your problem, or an off-the-shelf tool would do the job better and cheaper, we'll say so on the call.
Specific Commitments. Not Marketing Language.
Every firm claims to be reliable, fast, and senior. Here is what those words actually mean in practice when you engage with us.
Business ROI First. Technology Second.
We run an AI opportunity assessment before writing a line of code. Use cases are ranked by business impact, not technical novelty. If a simpler tool solves your problem, we will tell you.
Proof of Concept in 2 Weeks.
We validate the core AI approach with a working prototype before committing to a full build. Accuracy, latency, and cost are measured at the PoC stage. If the approach does not work, we tell you early.
Senior ML Engineers. No Generalists.
Our team has hands-on production experience with LLM integrations, RAG pipelines, vector databases, and custom ML models, not just prompt engineering tutorials.
Cost Controls Built In from Day One.
Semantic caching, prompt compression, model routing, and budget alerts are engineered into every integration. We design AI systems that are cost-predictable at scale, not just in demos.
Evaluation Frameworks, Not Vibes.
We do not ship AI features without a quality measurement framework. Accuracy, latency, and output quality are tracked continuously so you can trust what you have built and catch regressions early.
Your Data Stays Yours.
All models, pipelines, vector indices, and code are transferred to you at completion. We design architectures that work with your existing data stack without requiring you to replace infrastructure.
Dhananjay Goel
Founder & CEO, Enlight Lab
I started Enlight Lab because too many founders get sold senior engineers and handed juniors after they sign. That does not happen here.
I stay involved in every engagement, from the first scope call to launch. You work directly with the people who build your product, and the price we agree on is the price you pay.
- Senior engineers only, assigned from day one
- Fixed price, confirmed before any code is written
- Weekly demos and full source-code ownership
Free scoping call. Fixed-price proposal within 24 hours.
Partners & Recognition
Certified Partner Status & Ratings
Four Phases. Four Weeks. Every Checkpoint is Working Software.
No status-report theatre. No slide decks. At every phase you receive something you can read, test, or deploy.
AI Opportunity Assessment
We map your product to AI use cases ranked by business ROI, not technical novelty. You receive a prioritised roadmap with estimated impact per initiative and a data readiness assessment. A working document, not a buzzword deck.
Proof of Concept
A working prototype that validates the core AI approach before you commit to a full build. We measure accuracy, latency, and cost at the PoC stage. If the approach does not work, we tell you and help you find one that does.
Production Build
Full engineering with evaluation frameworks, monitoring dashboards, rate limiting, and cost controls built in from the start. Weekly demos show real AI output against real data, not mocked responses.
Monitoring and Iteration
AI systems degrade without attention. We configure evaluation pipelines, track model performance over time, and help you iterate based on real usage data rather than assumptions.
What Engineering & Product Leaders Say
Real feedback from our clients, from startups to large organisations.
From verified Clutch reviews and LinkedIn recommendations
Enterprise-Grade Tools.
Battle-Tested in Production.
Stack selection is driven by project requirements. We advise against over-engineering.
Tell Us About Your Project
30 minutes. We review your concept and send a fixed-price proposal within 24 hours of the call.
What to expect on your scoping call:
- Direct Engineering Scoping: Speak directly to a senior engineer. No salespeople, no scripted pitches.
- Fixed-Price Quote: Receive a detailed written scope and a fixed-price quote within 24–48 hours.
- Guaranteed Confidentiality: We sign a mutual NDA before we discuss any proprietary architecture or system logic.
Start With a Free Scoping Call
Tell us about your project and we’ll prepare a tailored scope and fixed-price proposal.
Frequently Asked Questions
Everything you need to know before booking a call.
Do you build with OpenAI, Anthropic, or open-source models?
How do you handle hallucinations and accuracy?
What if we don't have training data?
How much will LLM API usage cost in production?
Can you integrate with our existing product and data?
How long does an AI integration take?
How do I get started?
Ready to Start Your Project?
30 minutes. No pitch deck. We review your concept, define the scope, and send a fixed-price proposal within 24 hours of the call.