Kbylabs is a specialist software engineering and AI consultancy. We design production-grade LLM systems and architect robust software platforms for organizations that need deep technical expertise — not generalist advice.
import anthropic
import chromadb
# Hybrid retrieval + generation pipeline
client = anthropic.Anthropic()
db = chromadb.PersistentClient(
path="./chroma_store"
)
def answer(question: str) -> str:
docs = db.query(
query_texts=[question], n_results=5
)
context = "\n\n".join(docs["documents"][0])
return client.messages.create(
model="claude-opus-4-5",
system="Answer only from context.",
messages=[{"role": "user",
"content": f"{context}\n\n{question}"}]
).content[0].text
We don't claim to do everything. Kbylabs operates in two tightly coupled domains where genuine depth matters more than breadth — software engineering and applied LLM systems.
We design systems that are correct first, then fast. Whether you're starting from a greenfield or untangling a distributed monolith, we apply Domain-Driven Design, bounded context mapping, and explicit API contracts to produce architectures your team can reason about and extend without fear.
Velocity without discipline compounds technical debt. We build the internal platform layer — CI/CD, testing strategy, observability stack, and engineering standards — that lets your developers ship confidently and your systems degrade gracefully under unexpected load.
When a board needs confidence in an engineering org, or a startup needs senior technical leadership before a full-time hire, we step in. We perform structured codebase audits, architecture health reviews, and can serve as fractional CTO or VP Engineering during critical growth phases.
Integrating an LLM into a production system is a software engineering problem, not a prompt-writing exercise. We design the full stack: API integration (Anthropic, OpenAI), context window management, structured output schemas, tool-use patterns, cost optimization, and rate-limit-aware retry logic.
Most RAG prototypes fail in production because chunking, retrieval, and re-ranking are treated as defaults rather than design decisions. We build retrieval pipelines that handle document heterogeneity, query ambiguity, and knowledge freshness — evaluated rigorously with RAGAS before any deployment.
Autonomous agents that run reliably in production require deterministic scaffolding around non-deterministic models. We design multi-agent architectures with explicit state machines, tool registries, memory layers, and human-in-the-loop checkpoints — using LangGraph, CrewAI, or bespoke frameworks depending on the control requirements.
We'll tell you honestly whether we can help — and if not, who can. No sales pitch, no upsell. Just a direct technical conversation.
We operate with the discipline of a staff engineering team embedded inside your organization — not a vendor shipping deliverables into a void. Every engagement is grounded in clear outcomes, documented assumptions, and continuous stakeholder alignment.
Start the ConversationWe conduct structured interviews with technical and business stakeholders to map the existing architecture, surface constraints, and identify the highest-leverage intervention points before writing a single line of code.
We produce a high-fidelity system design — including data flows, component contracts, failure modes, and cost projections — that serves as the engineering contract between Kbylabs and your team throughout the engagement.
We ship in tight, reviewable increments with full observability from day one — metrics, tracing, and alerting are non-negotiable. No black-box deliveries; your team has visibility at every layer.
We close every engagement with comprehensive runbooks, architecture decision records (ADRs), and live knowledge-transfer sessions — ensuring your internal teams own and can evolve what we've built.
We're practitioners, not generalists. Every recommendation we make is grounded in hands-on experience shipping production systems at scale.
We treat every engagement as a software engineering problem — with formal specs, code review, and production-grade standards applied from the first commit.
No black boxes. Architecture decisions are documented, trade-offs are surfaced, and your team has direct access to every artefact we produce throughout the engagement.
Engagements are scoped around measurable outcomes — latency targets, cost reduction percentages, automation coverage ratios — not vague deliverable lists.
We work at the leading edge of LLM tooling, agentic frameworks, and AI infrastructure — applying what works in production, not what's trending in blog posts.
Kbylabs LLC is a specialist software engineering and AI consultancy founded on a simple thesis: the gap between a working prototype and a reliable production system is an engineering problem, not a product problem. Our practice is built around closing that gap — systematically, measurably, and with full technical transparency.
We operate as a focused technical partner, not a generalist agency. Engagements are staffed with senior-level expertise matched to the specific domain at hand — software architecture, LLM systems, or both. No bait-and-switch on seniority, no work delegated without your knowledge.
Deliverables are running, tested software — not slide decks. Every recommendation comes with a reference implementation or it doesn't come at all.
A system that does the wrong thing fast is worse than one that does the right thing slowly. We write correct code, then profile and optimize with evidence.
We integrate language models the same way we integrate a database — with contracts, failure modes, retries, and fallbacks. Prompt engineering without software engineering is a liability.
We write code your team can read, modify, and own without us. No proprietary frameworks, no black boxes, no artificial dependency on Kbylabs after the engagement ends.
Whether you're evaluating AI feasibility, scoping a complex migration, or need a senior technical partner to unblock a stalled initiative — we'll give you a candid, no-obligation assessment within 24 hours.
Jurisdiction
New Mexico LLC — United States of America
Initial response SLA
Within 24 business hours
All discovery conversations are confidential. We are fully prepared to execute mutual NDAs prior to any technical disclosure.