software · growth · AIRAG pipelines
Ingestion, chunking, embeddings, hybrid search and re-ranking. See RAG development.
AI harness & LLM apps
LLM application development that holds up in production.
Monocerix delivers LLM application development for teams moving AI from demo to production. We engineer the AI harness around the model: the tools it can use, the data it retrieves (RAG), the guardrails that keep it safe, the evals that prove it works and the monitoring that keeps it working.
Planner HawkCarmicaGreet NinjaPlanner HawkCarmicaGreet Ninja
Trusted by Planner Hawk, Carmica, Greet Ninja & more
Demo vs production
The model is 10%. The harness is the rest.
Generative AI development is easy to demo and hard to ship. In production, models face messy inputs, edge cases, cost limits, latency targets and real consequences when they are wrong.
An AI harness is the engineering around the model that makes it dependable: structured prompts, retrieval, tool permissions, validation, fallbacks, evals and observability.
- Grounded: retrieval from your approved data
- Controlled: tool permissions and AI guardrails
- Proven: LLM evals on real test sets
- Observable: tracing, cost and quality dashboards
What you get
What we engineer around the model.
Tools & agents
Typed tools with permissions, so agents act safely in your systems.
MCP servers
Expose your systems to AI assistants through the Model Context Protocol. See MCP servers.
AI guardrails
Input and output checks, PII handling, policy rules and safe fallbacks.
LLM evals
Test sets, automated scoring and regression checks before every release.
Observability
Tracing, cost, latency and quality monitoring in production.
Model strategy
The right model per task across Claude, GPT, Gemini and open models.
Security & privacy
Data minimization, access control, audit logs and regional hosting.
Continuous improvement
Feedback loops that turn failures into better prompts, data and tests.
How we work
From prototype to production.
Week 1–2
Define & measure
Use case, success criteria and an evaluation set.
Week 2–6
Build the harness
Retrieval, tools, guardrails and integrations.
Week 5–8
Evaluate
Scored testing, red-teaming and cost tuning.
Ongoing
Operate
Monitoring, evals on every change and improvements.
Markets we serve
Production AI within your rules.
Data protection and AI rules are tightening everywhere. We design for the regime you operate under.
UAE & Saudi
UAE and Saudi data protection laws, and regional hosting options.
UK & EU
GDPR and EU AI Act-aware design, documentation and human oversight.
US, Canada & Australia
Sector rules, SOC 2-friendly practices and audit trails.
India
DPDP Act-aware data handling, with India-region hosting and English and Hindi evals.
Thailand
PDPA-aware data handling and Thai-language evals and guardrails.
Buyer guide
LLM application development: common questions.
Why do AI pilots fail?
Usually not because of the model. They fail because nobody defined what good looks like, there was no test set, retrieval returned the wrong context, or the system had no way to catch and recover from mistakes.
What does it cost?
Taking an AI prototype to production typically costs $8,000 to $40,000 depending on data, integrations and risk. With us, AI harness work starts from $700 for clients outside India.
Fine-tuning or RAG?
For most business use cases, retrieval (RAG) with good prompts and tools beats fine-tuning: it is cheaper, easier to update and easier to audit. Fine-tuning helps for style, format or very specialized tasks.
Starting price: $700 (about AED 2,570) for clients outside India. Every project then gets a written, itemized quote. See all starting prices.
Specialist services
Need something more specific?
Your quotation
A quote built for your exact scope.
Answer a few questions about your LLM application and you'll get a formal, itemized quotation with scope, timeline, team and milestones, usually within 48 hours. Quotes in USD, AED, GBP or INR.
Plan my LLM app
WE'LL ASK ABOUT
- The AI use case and users
- Data sources and systems
- Quality, latency and cost targets
- Security and compliance needs
Takes about 4 minutes. Your answers are saved as you go.
Proof
See it working for Carmica.
Carmica
CarmicaCar care studio · Pune
From “who’s best for PPF in Pune?” to the answer AI gives.
Carmica sells premium PPF, ceramic and graphene coatings. We rebuilt the site around an instant quote builder and an 85 GU gloss guarantee. Then we added local SEO and AEO, and connected an AI harness that follows up every quoted lead on WhatsApp.
4-stepWhatsApp follow-up run by an AI agent
Instantonline quotes for cars & bikes
24/7lead response, with no lead left un-followed
FAQ
AI Harness & LLM Apps questions, answered.
Straight answers to what clients ask us most. Still curious? Ask us on WhatsApp.
What is an AI harness?
The engineering around a language model that makes it reliable in production: retrieval, tools, guardrails, evaluation and monitoring.
Which models do you work with?
Claude, GPT, Gemini and open models such as Llama and Mistral, chosen per task.
Can you fix our existing AI app?
Yes. We start by building an evaluation set, measure where it fails and fix the biggest causes first.
How do you stop hallucinations?
By grounding answers in retrieved sources, requiring citations, validating outputs, limiting scope and routing low-confidence cases to people.
Can the AI run in our own cloud?
Yes. We deploy in your cloud account and region, and can use private model endpoints.
Let's build something legendary
Ship AI you can trust.
Tell us about your AI use case and we'll send a production plan and quote.
Takes about 4 minutes Itemized, written quotation Reply within 2 working hours