The full AI stack. No hand-offs. No gaps.
From LLM engineering to agent systems, reliability infrastructure to strategic consulting, Karat Labs operates across every layer of the modern AI stack.
LLM Engineering
Prompt architecture, fine-tuning, RAG, agents, and structured outputs, engineered for production.
Building with language models is not just about calling an API. It is about designing the prompting architecture, managing context, structuring outputs, and ensuring the model behaves reliably at scale. We engineer LLM systems from first principles.
LLM Reliability & Evaluation
Evaluation harnesses, hallucination detection, red teaming, and observability, so your AI system earns trust.
Most AI systems fail in production not because the model is bad, but because no one built the infrastructure to catch when it stops being good. We build evaluation pipelines, reliability frameworks, and observability tooling that let you ship AI with confidence.
Agent Engineering
Autonomous agents, multi-agent systems, planning loops, and agentic workflows, built to act, not just respond.
Agents are the next frontier of LLM engineering, systems that do not just answer questions but plan multi-step tasks, use tools, coordinate with other agents, and operate autonomously within defined boundaries. We design and build agents from architecture through evaluation, with reliability built in from the start.
AI Infrastructure & MLOps
Deployment, vector databases, inference optimisation, and cost management, for AI systems that run at scale.
Great AI systems need great infrastructure. We handle the engineering layer that keeps AI running: model deployment, vector database setup, embedding pipelines, inference optimisation, and the observability tooling that tells you when something goes wrong before your users do.
Research & Prototyping
Proof-of-concept builds, feasibility studies, and applied ML research, before you commit to the build.
Not every AI idea is ready for a full product build, and discovering that six months in is expensive. We run rapid prototyping engagements and applied research sprints to test feasibility, surface unknowns, and give you a clear technical picture before any major investment.
AI Consulting & Strategy
Use case discovery, AI readiness assessment, build-vs-buy analysis, for organisations getting serious about AI.
Before you build, you need to know what to build, and whether you are ready to build it. We run structured consulting engagements to help teams identify the highest-value AI opportunities, assess their data and infrastructure maturity, and make informed decisions about vendors, models, and approaches.
How an engagement works.
Discovery
We understand the problem, the data, the constraints, and what success actually looks like.
Architecture
We define the approach: model selection, system design, evaluation criteria, and delivery plan.
Build
We engineer the system, iterating against defined quality benchmarks throughout.
Evaluate
We run the eval harness, red team the system, and validate before any handoff.
Deploy
We handle infrastructure, monitoring, and go-live support.
Iterate
AI systems improve over time. We build with that in mind.
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