You don't need another prompt-engineer playing with ChatGPT. You need an engineer who can wire LangChain Expression Language into a real codebase, manage agent state with LangGraph, evaluate quality with LangSmith, and hand your team a system that survives traffic, edge cases, and a model swap. That's what we do.
$18/hr
Starting rate
3 days
Free PoC delivery
120+
LLM apps shipped
Brief us in 60 seconds. We'll match a senior LangChain engineer in 24 hours and offer a free 3-day proof of concept.
Replies within 4 business hours · No agency fee
Six things we've shipped in the last twelve months — none of them are chatbots that say "Hello, I'm an AI."
LangGraph workflows that decompose a research question, call 6–10 tools in parallel (search, scrape, parse, summarize, verify), checkpoint state in Postgres, and stream the final brief over WebSocket. Used for legal due diligence and competitor analysis.
Hybrid retrieval (BM25 + dense + reranker) over Confluence, SharePoint, Salesforce, and PDF chaos. Ingestion pipelines that handle PowerPoints, scanned receipts, and 800-page contracts. Citations that actually point to the source.
Embedded copilots that query your product database, call your APIs, draft emails, and explain dashboards — built with LangChain tool-calling, scoped permissions per user, and full audit trails for SOC 2.
Invoice extraction, contract review, claims triage, KYC verification. LangChain orchestrates OCR → classification → field extraction → validation → human-review queue. We’ve replaced 3-week BPO turnaround with 4-minute pipelines.
LangChain agents wired to Twilio, Vapi, or Retell for inbound and outbound calls. Sub-second latency with streaming, tool calls to your CRM, and full transcripts piped to LangSmith for review and evaluation.
Custom eval harnesses on top of LangSmith — golden datasets per use case, regression suites, prompt diff dashboards, and A/B tests that compare GPT-4o vs Claude vs your fine-tuned model on your real workload.
Hands-on production experience with the full ecosystem — not just the quick-start docs.
Our process is built around removing risk before you commit. Every project starts with a free proof of concept so you see working code in the first week.
30-minute scoping call. We map your use case, models, data sources, and constraints, and pull 1–2 senior LangChain engineers from our bench whose past work matches.
Working code, not a deck. The engineer builds a minimal end-to-end slice — typically one chain or one agent — wired to your real data and visible in LangSmith.
We commit to a fixed scope or dedicated-engineer model. Daily standups in your Slack, code in your repo, PRs reviewed by your team. LangSmith dashboard shared from day one.
Once shipped, we instrument golden datasets, set quality thresholds in CI, and either continue as fractional ML engineers or hand off cleanly to your team with a runbook.
Three engagement models. No setup fees, no agency margin, no minimum commitment beyond the current sprint.
3 days
Free
End-to-end slice of your use case, working against your real data, visible in LangSmith. Zero commitment.
4–12 weeks
$12K – $60K
Defined deliverable, fixed price, fixed timeline. Best when you know what to build and need it shipped.
Monthly
$18 – $28/hr
Fractional or full-time LangChain engineer embedded in your team. Best when scope is evolving.
We're not a generic dev shop with an AI page. AI is the practice — and LangChain has been our default LLM framework since v0.0.150.
Every engineer ships a LangGraph workflow and an LCEL composition during interview — no whiteboard puzzles.
We’d rather show you working code than convince you with a deck. If the PoC isn’t great, we walk away — no invoice.
Every project includes traces, evals, and dashboards in LangSmith. You see exactly what the model sees.
We’ll tell you when LangChain is overkill and you should just use the OpenAI SDK directly. Honest scoping.
A generic Python engineer can call OpenAI in a script. A LangChain developer ships production LLM applications — they design composable chains with LCEL, manage agent state with LangGraph, evaluate quality with LangSmith, swap models without rewriting business logic, and handle the messy parts: token limits, retries, streaming, callbacks, and observability. The work product is an app you can hand to a team and scale, not a notebook.
Yes. Our developers know when LangChain is the right choice and when it adds overhead. They are equally comfortable with LlamaIndex for retrieval-heavy use cases, the OpenAI Assistants API for stateful agents, the Anthropic Claude SDK for tool-use workflows, and raw HTTP for simple completions. We pick the framework that matches the project — not the other way around.
LangGraph is our default for any workflow involving branching logic, human-in-the-loop, retries, or long-running state. Our team has shipped production LangGraph workflows for document review, customer support routing, sales-call coaching, and financial reconciliation. We checkpoint state with Postgres or Redis so workflows survive restarts.
We instrument every project with LangSmith from day one. We build evaluation datasets from real user inputs, run regression tests on prompt and model changes, track latency and token cost per chain step, and set up alerts on quality drift. For domain-specific apps we add LLM-as-judge evals plus human review on a sample.
Model-agnostic by default. We use the BaseChatModel abstraction so your application can switch between OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Azure OpenAI, or open-source models on Together / Fireworks / Groq with a config change. We also build cost-routing logic so cheap requests go to small models and complex ones escalate.
Full delivery. We deploy to AWS Lambda, ECS, Cloud Run, Kubernetes, Vercel, or your own VPC. We add LangServe or FastAPI for HTTP serving, set up streaming responses, configure rate limiting and circuit breakers, and ship dashboards in LangSmith and Datadog. You get a production system, not a GitHub repo.
Most LangChain engagements run as fixed-scope projects (4–12 weeks, $12K–$60K) or dedicated engineers ($18–$28/hr depending on seniority and US/India mix). We start almost every project with a free 3-day proof of concept so you see working code before signing anything.
Brief us on what you're building. We'll match a senior engineer in 24 hours and ship a working slice by the end of the week — free.