Enterprise AI engineering, model development, evaluation, and deployment.
Acadify Solution builds practical AI systems for companies that need to move from prototype to production. Our public engineering work covers LLM evaluation, fine-tuning, RAG systems, autonomous agents, AI security, and deployment infrastructure.
Website: https://acadifysolution.com
AI Platform & Labs: https://ai.acadifysolution.com/
Engineering & AI Blog: https://acadifysolution.com/blogs
GitHub: https://github.com/AcadifySolution
LinkedIn: https://www.linkedin.com/company/acadify-solutions/
General: hello@acadifysolution.com
| Area | Focus |
|---|---|
| LLM Engineering | Fine-tuning, LoRA/QLoRA, model adaptation and deployment |
| AI Evaluation | Accuracy, semantic similarity, grounding, safety, regression testing |
| RAG | Retrieval pipelines, document processing, vector search and reranking |
| AI Agents | Tool use, orchestration, validation and reliable workflow execution |
| AI Security | LLM gateways, PII protection, prompt-risk controls and auditability |
| Cloud AI | AWS, GCP, Docker, Kubernetes and Terraform-based infrastructure |
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AI Evals Framework — repeatable evaluation of LLM and RAG outputs with correctness, semantic, grounding and safety metrics.
https://github.com/AcadifySolution/ai-evals-framework -
LLM Security Proxy — security gateway for LLM traffic with request controls, PII handling, guardrails and audit logging.
https://github.com/AcadifySolution/llm-security-proxy -
Fine-Tuning Pipeline — LoRA/QLoRA SFT pipeline with Accelerate, DeepSpeed and SageMaker deployment scaffolding.
https://github.com/AcadifySolution/fine-tuning-pipeline -
Enterprise RAG Boilerplate — production-oriented RAG reference architecture and implementation patterns.
https://github.com/AcadifySolution/enterprise-rag-boilerplate -
Autonomous Agent Swarm — orchestration patterns for multi-agent workflows, retries, checkpoints and operational controls.
https://github.com/AcadifySolution/autonomous-agent-swarm -
ASR Feedback — structured evaluation and feedback infrastructure for AI systems.
https://github.com/AcadifySolution/asr-feedback
https://ai.acadifysolution.com/
Our AI platform and lab environment for LLM evaluation, RAG, AI architecture reviews, reliability evaluation and related platform work.
AI Platform & Labs: ai@acadifysolution.com
https://acadifysolution.com/blogs
Articles and technical content covering AI engineering, LLMs, RAG, evaluation, security, development and practical implementation.
Proposals, scoping, quotes, custom statements of work, dedicated engineering pods and enterprise MVP delivery.
Technology alliances, cloud reseller partnerships and executive co-development engagements.
LLM evaluation, RAG, platform sandbox, architecture reviews and reliability evaluations.
Engineering pods, AI engineers, full-stack architects and DevSecOps opportunities.
General inquiries, event invitations, press outreach and technical queries.
We focus on systems that are:
Reliable — deterministic checks, validation, failure handling and regression coverage.
Observable — useful telemetry, evaluation reports and operational signals.
Secure — least-privilege infrastructure, secrets hygiene and protection of sensitive model data.
Practical — architecture chosen around the actual product, workload and deployment constraints.
Explore the public repositories for reusable reference implementations, evaluation patterns, infrastructure examples and engineering practices.
For implementation, architecture, AI evaluation, model pipelines or deployment work:
sales@acadifysolution.com
https://acadifysolution.com
Public repositories describe representative engineering work. Specific client engagements, metrics, infrastructure and security controls may vary by project and are not disclosed unless authorized.
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