What Codersarts AI Does
Codersarts AI is the custom AI/ML development and consulting arm of Codersarts — built for businesses, startups, and product teams that need production-grade AI systems, not demos.
Core Services
1. LLM Integration
Integrating large language models into your existing product or workflow.
OpenAI, Anthropic, Gemini, Mistral, LLaMA integration
Custom prompt engineering and chain design
Streaming, function calling, and tool use
Multi-turn conversation and memory management
Cost optimisation and model routing
2. RAG System Development
Building retrieval-augmented generation pipelines that give your LLM access to your data.
Document ingestion pipelines (PDF, HTML, CSV, databases)
Vector store setup — Pinecone, Weaviate, Chroma, pgvector
Hybrid search — semantic + keyword
Re-ranking, chunking strategy, and context compression
Evaluation and hallucination reduction
3. Agentic AI & Autonomous Workflows
Building AI agents that reason, plan, and take actions.
ReAct and tool-calling agent architectures
Multi-agent orchestration — CrewAI, LangGraph, AutoGen
Custom tool and API integrations
Human-in-the-loop workflows
Agent monitoring and observability
4. Custom ML Model Development
Building and training models tailored to your data and problem.
Classification, regression, time-series forecasting
NLP — sentiment analysis, entity extraction, summarisation
Computer vision — detection, segmentation, classification
Anomaly detection and predictive maintenance
Model fine-tuning on proprietary datasets
5. MLOps & AI Infrastructure
Deploying and maintaining AI systems in production.
Model serving — FastAPI, BentoML, TorchServe
CI/CD pipelines for ML workflows
Model versioning and experiment tracking — MLflow, W&B
Monitoring — drift detection, performance degradation alerts
Cloud deployment — AWS, GCP, Azure
6. AI Consulting & Architecture Review
For teams that need strategic guidance, not just code.
AI readiness assessment
Architecture design for new AI features
Tech stack selection and vendor evaluation
Code and pipeline review for existing AI systems
Fractional AI lead — ongoing advisory engagement
7. POC & MVP Development
For founders and product teams validating an AI-powered idea.
Scoped proof-of-concept in 1–2 weeks
Functional MVP with core AI features in 4–6 weeks
Handoff-ready code with documentation
Post-launch support available
Industries Served
SaaS & Product Companies — Adding AI features to existing products
Startups — Building AI-first products from scratch
Enterprises — Internal automation, document processing, knowledge management
Healthcare — Clinical NLP, medical imaging, patient data analysis
Finance — Fraud detection, risk scoring, document extraction
EdTech — Personalisation engines, AI tutors, assessment automation
Engagement Models
Model | Best For |
Project-based | Defined scope — POC, MVP, single feature |
Retainer | Ongoing development and iteration |
Fractional AI Lead | Strategy + architecture without a full-time hire |
Team Augmentation | Embedding AI engineers into your existing team |
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