AI Automation Agency for Companies That Want Working Systems, Not Demos
Macronimous is an AI automation agency built on a 24-year web engineering practice in India, delivering LLM integrations, RAG knowledge systems, and AI agents to businesses and digital agencies in the United States, United Kingdom, and Australia. Development runs USD 25 to 30 per hour, dedicated AI engineers from USD 2,500 per month, with white-label delivery for agencies.
What does an AI automation agency actually do?
An AI automation agency designs, builds, and maintains software that puts large language models to work inside a business. In practice that means three things: connecting models like GPT and Claude to your existing products and data, building retrieval systems (RAG) that answer from your own documents instead of the open internet, and deploying agents that complete multi-step tasks such as processing orders, routing leads, or assembling reports.
Search the term and half of what ranks is people teaching you how to start one. Course launches, YouTube funnels, Instagram reels about six-figure retainers. That wave has a consequence for buyers: the market is crowded with two-person shops founded after ChatGPT, reselling no-code templates at agency prices, gone in eighteen months. We sit on the other side of that line. Macronimous has been an engineering company since 2002, with 50+ developers across WordPress, Magento, React, and custom PHP. The AI practice is built on that bench, not instead of it.
What we build
We claim three tiers of AI work, and only three. Each one is delivered by the same engineers who build and maintain production web systems for US, UK, and Australian clients.
1. LLM integration and orchestration
Wiring OpenAI and Anthropic models into the products you already run: WordPress sites, Magento and WooCommerce stores, React and Next.js apps, custom PHP platforms. The work is API orchestration, prompt pipelines, structured outputs, token cost control, and evaluation harnesses so you know when a model update quietly degrades your feature. Most “AI features” fail not at the model but at this plumbing layer. That is the part we are good at, because it is ordinary software engineering with new failure modes.
2. RAG and knowledge systems
Private assistants grounded on your own content: support bots that answer from your documentation, internal Q&A over contracts and SOPs, product finders that search your actual catalog. We handle chunking strategy, embedding pipelines, vector search with pgvector or Pinecone, citation of sources in every answer, and the hallucination controls that separate a useful assistant from a liability. A RAG system is only as good as its retrieval layer, so that is where the engineering hours go.
3. AI agents and workflow automation
Multi-step agents and n8n workflows that take real work off your team: order exception handling, catalog operations, lead qualification and routing, report assembly, inbox triage. Agents get scoped narrow and instrumented heavily. An agent that does one back-office job reliably beats a general assistant that does ten jobs at 80 percent, because the 20 percent is where your staff stops trusting it.
What we deliberately do not do: model fine-tuning and pretraining. Most business problems are retrieval and orchestration problems, and fine-tuning adds training cost, evaluation burden, and permanent maintenance for gains that rarely survive the next base-model release. If your case genuinely needs a fine-tuned model, we will tell you so and point you to a team with ML engineers on staff. An AI vendor that claims every tier of the stack is telling you something about their sales process, not their engineering.
Macronimous vs. the typical AI automation shop
AI development pricing
Fixed-price searchers and dedicated-team buyers want a number before a call, so here are ours.
Hourly
USD 25-30 per hour. Best for scoped features, integration sprints, and audits of AI work another vendor left behind. Billed against tracked hours with weekly summaries.
Dedicated AI Engineer
USD 2,500-4,000 per month by seniority, full time at 160 hours. For ongoing automation programs and agencies reselling AI delivery. Includes PM coordination and monthly reports.
Paid 2-Week Pilot
80 hours at USD 25/hr flat (USD 2,000 total). One concrete scope, real production work, full code handover. Evaluate us on output before any monthly commitment.
Fixed-price project quotes are provided after a discovery call, once the scope is specific enough to price honestly. We do not quote AI projects from a contact form description.
The stack we build on
OpenAI and Anthropic APIs for models. LangChain or LlamaIndex where orchestration complexity earns the dependency, plain SDK code where it does not. n8n for workflow automation. Postgres with pgvector as the default vector store, Pinecone or Qdrant when scale demands it. React and Next.js on the front, WordPress, Magento, PrestaShop, and custom PHP as the integration surface, because that is where our clients’ businesses already live.
We default to boring, inspectable stacks. If a Postgres table and a cron job solve the problem, we will not sell you an agent. And your data handling is contractual, not hand-waved: see our policy on whether client source code is sent to third-party AI services before you ask, because you should ask every vendor that question.
White-label AI automation for agencies
Most of our revenue for 24 years has come from delivering behind other agencies’ brands. Design studios, marketing agencies, and dev shops in the US, UK, and Australia sell the project; we build it under NDA, in their tooling, invisible to their client. AI automation slots into that same model. If your clients are asking for chatbots, RAG assistants, or workflow automation and you do not want to hire ML-adjacent engineers on your payroll, you quote the work and we deliver it under your brand. Same terms as our white-label SEO delivery: your client relationship stays yours.
How an engagement starts
Step 1, Discovery (Day 0-3). You send the workflow you want automated or the feature you want built. We respond with clarifying questions and an honest read on whether AI is the right tool. Sometimes it is not, and we say so.
Step 2, Scope and quote (Days 3-7). A written scope: what gets built, what data it touches, what the model costs will run monthly, and the price. Model usage costs are itemized separately from our fees so you see both.
Step 3, Pilot or contract (Week 2). Start with the paid 2-week pilot on a concrete scope, or go straight to an hourly or dedicated engagement. NDA and IP transfer are signed before the first commit either way.
Step 4, Build with checkpoints (Weeks 2-8). Working demos at each checkpoint, built in your repository. For RAG and agent work, an evaluation set is part of the deliverable, so quality is measured, not vibes.
Step 5, Handover or continue (Week 8+). Full handover with documentation, or roll into a maintenance retainer. Model APIs change monthly; someone has to own that, and it can be us or your team.
Send us one workflow you want automated.
Email [email protected] with the process, the systems it touches, and roughly how many hours it eats per week. You get an honest read within one business day, including “AI is the wrong tool for this” when that is the answer.
Frequently asked questions
What does an AI automation agency do?
An AI automation agency builds and maintains software that applies large language models to business operations: integrating models like GPT and Claude into existing products, building RAG systems that answer questions from a company’s own documents, and deploying agents that execute multi-step tasks such as lead routing, order processing, and report generation. At Macronimous the work is delivered by web engineers who also build the WordPress, Magento, and React systems the AI connects to, which matters because most AI project failures happen in the integration layer, not the model.
How much does an AI automation agency charge?
Rates vary widely across the market, from USD 25/hr offshore to USD 200+/hr for US consultancies. Macronimous charges USD 25-30 per hour, with dedicated AI engineers at USD 2,500-4,000 per month full time (160 hours). A paid 2-week pilot is available at USD 25/hr flat, 80 hours total, so you can evaluate real output before a monthly commitment. Model usage costs (OpenAI, Anthropic API fees) are itemized separately in every quote, because hiding them in the service fee makes both numbers dishonest.
Do you build custom AI models, or integrate existing ones?
We integrate and orchestrate existing models. Our scope covers three tiers: LLM integration and orchestration, RAG and knowledge systems, and AI agents with workflow automation. We deliberately do not offer model fine-tuning or pretraining, because most business problems are retrieval and orchestration problems, and fine-tuning adds permanent maintenance cost for gains that rarely survive the next base-model release. If your case genuinely requires a fine-tuned model, we will say so during discovery and refer you to a team with ML engineers.
What tools and platforms do you use for AI automation?
OpenAI and Anthropic APIs for models. n8n for workflow automation. Postgres with pgvector as the default vector store, with Pinecone or Qdrant when scale requires it. LangChain or LlamaIndex only when orchestration complexity justifies the dependency. Frontends in React and Next.js, integrations into WordPress, Magento, WooCommerce, PrestaShop, and custom PHP platforms. The stack is chosen to be inspectable and portable: everything we build runs in your accounts and your repository, not on a proprietary platform you cannot leave.
Is our data sent to OpenAI or Anthropic when you build RAG systems?
Only the content required at query time, under API terms where your data is not used for model training (both OpenAI and Anthropic offer this on their API tiers, distinct from their consumer products). Document stores and vector databases live in your infrastructure or your cloud accounts. Where requirements are stricter, we architect for redaction layers or region-pinned deployments. Data handling is written into the contract, and we sign NDAs before discovery, not after.
Do you offer white-label AI automation for agencies?
Yes, and it is the engagement model we know best. Macronimous has delivered white-label development behind US, UK, and Australian agencies for 16 years. For AI work that means your agency sells and owns the client relationship, we build chatbots, RAG assistants, or automation workflows under NDA in your tooling, and your client never hears our name. Your client relationships are contractually protected: we do not contact or solicit your end clients.
Who owns the code, prompts, and workflows you build?
You do, 100 percent. Work happens in your Git repository from the first commit. Source code, prompt libraries, n8n workflow exports, evaluation sets, and infrastructure configuration are all covered by a written IP transfer clause. There is no retained IP, no licensing on custom work, and no platform dependency that keeps you paying us to keep what you already bought. If you leave, you leave with everything running.
How do I vet an AI automation agency before hiring one?
Ask four questions. One: what did you build before 2023? A vendor with no pre-AI engineering history has no track record you can verify. Two: what do you refuse to build? A shop that claims every AI capability is selling, not scoping. Three: who owns the prompts and workflows when we part ways? If the answer involves their platform, you are renting, not buying. Four: can I see rates before a call? Hidden pricing usually means the price depends on how the call goes. We publish our answers to all four on this page.
Related Questions
Start with the 2-week pilot.
80 hours at USD 25/hr flat on one concrete scope. Real production work, full code handover, no obligation to continue. If we are the wrong fit, you find out for USD 2,000, not after a 6-month retainer.
