# AiGanak

> AiGanak is an AI workflow automation and systems studio in Pune, India. It builds multi-agent workflows on n8n and Make, prompt guardrails, private model deployments and custom small language model proofs of concept, and runs LLM cost and reliability audits for companies in the US, Europe and India.

Last updated: 2026-10-23. Legal name: AiGanak Technologies OPC Pvt Ltd. Founder: Akshay Bankar.

## Key facts
- Legal name: AiGanak Technologies OPC Pvt Ltd (https://aiganak.com/about/)
- Location: Pimple Saudagar, Pune, Maharashtra 411027, India (https://aiganak.com/about/)
- Founded: 2021 (https://aiganak.com/about/)
- Founder: Akshay Bankar, Founder & Director, Enterprise AI Architect (https://aiganak.com/akshay-bankar/)
- Markets: US, Europe and India (https://aiganak.com/about/)
- AiGanak-SLM-1B status: Phase 2 convergence, not released (https://aiganak.com/slm-1b/)
- AiGanak-SLM-1B size: About 1 billion parameters, decoder-only, 128k-token context (https://aiganak.com/slm-1b/)
- LLM Cost Audit pricing: Quick Check free; Standard $1,500; Deep $4,500; implementation from $5,000; monitoring from $500 a month (https://aiganak.com/llm-cost-audit/)
- Audit turnaround: Five to seven working days (https://aiganak.com/llm-cost-audit/)
- Live products: Prompt Lab, Model Lab, Hiboto (https://aiganak.com/services/)

## Pages
- [AiGanak: private AI agents, LLM cost engineering and SLM research](https://aiganak.com/): AiGanak is a Pune-based AI systems studio. It builds multi-agent workflows, prompt guardrails and private model deployments, runs LLM cost and reliability audits, and researches small language models such as AiGanak-SLM-1B.
- [LLM Cost & Reliability Audit](https://aiganak.com/llm-cost-audit/): The LLM Cost & Reliability Audit measures your OpenAI, Anthropic, Azure, Bedrock or Gemini usage from your own logs, prices every saving (model routing, caching, prompt trimming, retrieval, batch) against your approved answers, and ranks reliability risks. A free Quick Check gives an instant estimate.
- [Sample LLM cost audit report](https://aiganak.com/llm-cost-audit/sample-report/): A sample audit for Orvella, a fictional support-software company spending $14,001 a month on LLM APIs. It finds $5,851 to $7,377 a month in savings (42 to 53 percent) through 9 changes and lists 4 reliability issues. All data is simulated.
- [AI engineering services](https://aiganak.com/services/): AiGanak builds production AI systems: multi-agent workflow automation on n8n and Make, prompt hardening and guardrails, private model deployment, and custom small or large language model development delivered as proof of concept, MVP and production.
- [Multi-agent workflow automation (n8n and Make)](https://aiganak.com/services/workflow-automation/): AiGanak builds n8n and Make multi-agent workflows that connect databases, CRMs, ERPs and messaging to language models with stateful routing, guardrails and cost tracking.
- [Prompt hardening and LLM guardrails](https://aiganak.com/services/prompt-guardrails/): AiGanak hardens LLM integrations against prompt injection, format failures and token waste using XML-structured prompts, negative constraints, input isolation and CI validation, backed by Prompt Lab diagnostics.
- [Private and on-premise LLM deployment](https://aiganak.com/services/private-model-deployment/): AiGanak deploys and optimises open-weight language models in a client's own cloud account or on-premise, including offline setups, so enterprise data never reaches public AI APIs.
- [Custom small language model development](https://aiganak.com/services/custom-slm-development/): AiGanak builds domain-specific small and large language models in stages: a proof of concept on sample data with an evaluation report, an MVP for a pilot team, then private production deployment. The work uses the training pipeline built for AiGanak-SLM-1B.
- [Prompt Lab](https://aiganak.com/prompt-lab/): Prompt Lab audits a failing system prompt. You submit the prompt, the failed input and output, formatting rules and a target answer; it checks XML structure, negative boundaries and injection risks and emails a diagnostic report.
- [Model Lab](https://aiganak.com/model-lab/): Model Lab benchmarks fine-tuned and candidate models against production baselines on your own examples, scoring accuracy, drift, hallucination and latency, and emails a performance report.
- [AiGanak-SLM-1B](https://aiganak.com/slm-1b/): AiGanak-SLM-1B is AiGanak's in-house 1-billion-parameter decoder-only small language model with a 128k-token context window, built first for logistics and supply-chain documents. It is in Phase 2 convergence and has not been released.
- [Hiboto](https://aiganak.com/hiboto/): Hiboto is AiGanak's no-code chatbot builder for creating bot profiles and chatbots.
- [Model Registry](https://aiganak.com/registry/): The AiGanak Registry gives validated partners early access to sandbox model releases, local-weights documentation and 128k-context test suites once they are available.
- [About AiGanak](https://aiganak.com/about/): AiGanak Technologies OPC Pvt Ltd is an AI systems engineering and research company in Pimple Saudagar, Pune, founded in 2021 by Akshay Bankar.
- [Akshay Bankar, Founder and AI Architect](https://aiganak.com/akshay-bankar/): Akshay Bankar is the founder and director of AiGanak, an enterprise AI architect with more than 16 years in software architecture, specialising in small language models, secure on-premise AI and agentic systems.
- [Contact and project scoping](https://aiganak.com/contact/): Contact AiGanak to scope a project. AiGanak Agent asks a few questions and drafts a proposal with an approach, timeline and estimate, which an engineer then reviews with you.
- [AiGanak facts](https://aiganak.com/facts/): Verified facts about AiGanak, its services, products, model research status and pricing, kept current for people and AI assistants.

## Optional
- [Full text for language models](https://aiganak.com/llms-full.txt)