AI consulting and development
AI consulting and AI development services that ship to production
By Yash Soni, Founder & CEO, Apex36Updated
In short
Apex36 is an AI consulting and AI development company. We find where AI pays off in your product or operations, then build it: RAG search, AI agents and integrations with the systems you already run. Projects start from $8,000 and you own the code. We have built production AI for legal tech, pharma and healthcare teams.
Key facts
| Starting price | From $8,000 per project |
|---|---|
| Typical timeline | Discovery typically in under a week; first shippable milestone typically in 1 to 3 weeks |
| Engagement model | Fixed-scope project, or a monthly team |
| Markets | US, UK, Australia, Singapore, UAE |
| Stack | Python, Node.js, TypeScript, OpenAI, Claude, Pinecone, PostgreSQL, AWS (EKS, Bedrock, Lambda), GCP, Langfuse |
Enterprise AI solutions
Enterprise AI works when it is tied to one workflow, one data source and one measure of success. We start there: which task, what data, what an acceptable answer looks like. Then we build the smallest version that proves it and grow it into a production system with monitoring, cost limits and a runbook your team owns.
AI agent development
An AI agent takes steps on its own: it reads a request, calls tools or APIs, checks the result and continues. We build agents for clear, bounded jobs, with logs of every step, limits on what each tool may do and a human hand-off when the agent is unsure. For BlackBox AI we contributed a multi-agent runner where several coding agents attempt one task and a judge picks the winning result.
RAG and LLM applications
Retrieval-augmented generation (RAG) lets a model answer from your own documents and cite them. We build the full pipeline: ingestion, chunking, embeddings, a vector database, retrieval with re-ranking, and an evaluation set that shows whether answers are right. DecoverAI's legal platform runs RAG over case documents on Pinecone and AWS EKS.
AI integration services
Most AI value comes from plugging a model into systems you already use: your CRM, inbox, document store or ERP. We build those integrations with proper authentication, retries and audit logs, so AI output lands where your team works instead of in a separate chat window.
Private and on-premise LLMs
When data cannot leave your environment, we set up the model inside your own cloud account or on your servers. Read the private LLM guide for costs, model options and how a deployment works.
AI guardrails and evaluation
Every AI system we ship has guardrails and tests. Guardrails check inputs and outputs: blocked topics, personal data, answers without a source, and spend limits. Evaluations run a fixed set of real examples on every change, so you know when a prompt or model update makes answers worse. Low-confidence cases go to a person instead of guessing.
AI consulting and readiness
Not sure where AI fits yet? Start with our free AI readiness assessment. Answer five questions about your product, data and stack, and we email you a written view of what to automate first, what to skip and whether your data is ready.
Proof from our work
Legal Tech · eDiscovery
DecoverAI
Legal AI platform with RAG over case documents on Pinecone and AWS EKS. DecoverAI raised a $2M+ seed; their platform runs at 10+ US law firms.
Read the case studyHealthTech · Pharma
Pharma workflow SaaS on AWS
An invite-only email triage workflow SaaS for a pharma startup, on multi-account AWS CDK with Langfuse LLM observability.
Read the case studyDevTools · Multi-Agent
BlackBox AI
Our contribution to a multi-agent coding platform: the multi-agent runner and judge, work on the LLM router and billing logic, and GCP code-execution sandboxes.
Read the case studyDevTools · PM AI
Mappie AI
An AI product management copilot that turns messy requirements into dev-ready epics and user stories, live at mappie.ai.
Read the case studyMedshield (our own product)
Local-first PHI de-identification that runs inside the customer's VPC or on-premise. Private beta.
Visit the site
What clients say about working with us
“One of the hardest-working and meticulous engineers I have encountered... helped build the infrastructure and Generative AI platform that is now deployed in large law firms throughout the United States... We eventually raised 2M+ in funding with the help of his efforts.”
“Excellent Full-Stack AI/LLM Developer. I worked with Yash from Apex 36 Technology Services on a Python and React AI/LLM project, and he delivered outstanding work.”
Frequently asked questions
At Apex36, AI development projects start from $8,000 for a first production use case, such as a RAG assistant on your documents. Larger systems with several integrations, agents or private hosting cost more, and you get a fixed quote in writing after discovery.
Discovery typically takes under a week, and the first shippable milestone typically lands in 1 to 3 weeks, depending on data access and scope. We ship in weekly iterations with a demo and a written changelog each week.
We use the model that passes your evaluation at the lowest cost: OpenAI, Claude, Gemini or open-weight models such as Phi. Some systems route different steps to different models.
Your data stays in accounts you control. We can run models inside your own AWS, Azure or GCP account or on your servers, and model costs are billed to your accounts. We set up providers so your data is not used for training, and models you host never send data out.
A chatbot answers questions. An AI agent takes actions: it calls tools and APIs, checks results and works through a task in steps. Agents need tighter limits and logging, which we build in from the start.
We ground answers in your documents with RAG, require a source for factual answers, add guardrails on inputs and outputs, and run an evaluation set on every change. When the system is unsure, it hands the case to a person.
Yes. We work in your repositories and tools, demo every week, write documentation as we go and hand over code your team owns. Several clients have kept us on as a monthly team after the first build.
Find out what to build first
Start with the free AI readiness assessment and get a written report by email, or book a 30-minute strategy call with the founder.