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I will build production grade ai agents and agentic workflows
Sauraabh M
Über diesen Service
Welcome to Softogram Your Production-Grade AI Architecture & Agent Studio.
Are you looking to deploy intelligent AI solutions that safely run in production? Most developers build basic API wrappers that fail under real-world scenarios due to severe hallucinations and weak state retention. We engineer highly resilient multi-agent pipelines and custom orchestrators designed for absolute durability, predictability, and business automation.
Our Specialized AI Focus:
- Autonomous AI Agents: Single or multi-agent systems using enterprise frameworks like LangGraph and CrewAI.
- Advanced Orchestration: Complex state management, custom tool callings, and long-term memory structures.
- RAG & Vector Infrastructures: Setting up hybrid vector search pipelines utilizing pgvector, Qdrant, or Pinecone.
- AI Safety & Guardrails: Deploying runtime evaluation barriers to prevent prompt injection and guarantee structured JSON outputs.
Why Softogram? We prioritize production readiness. Every system we ship features a Git-first approach with well-documented codebases, containerized infrastructure, and complete post-launch observability alignment.
Let's build something brilliant Message us to discuss your agent
Lerne Sauraabh M kennen
Sauraabh M
SDE2
- AusIndien
- Mitglied seitJan. 2023
- ⌀ Antwortzeit2 Stunden
Sprachen
Englisch, Hindi, Französisch
I am a results-oriented Backend Software Engineer with a solid foundation of three years in the field. My expertise lies in SDK development and backend optimization, utilizing languages like Java and Golang to create high-performance solutions. I have a proven ability to enhance system efficiency. My core passion is to design and develop robust, scalable systems that can effectively handle advanced features such as Vector Search for AI/ML workloads. I am dedicated to delivering top-tier software solutions that align with business objectives and drive user satisfaction.
Mein Portfolio
FAQ
What frameworks and tools do you use for AI agent orchestration?
We build production-grade agentic workflows using industry-standard Python frameworks like LangGraph and CrewAI. This allows us to create graph-based, multi-agent systems with deterministic control paths and robust state management
How do you ensure AI agents output structured data instead of random text?
We enforce strict schema control at the structural level. By configuring function calling parameters and integrating validation libraries like Pydantic, we guarantee the agents return predictable, well-formatted JSON payloads that your core application can easily parse.
Do you handle long-term memory and context optimization for the agents?
Yes. We build durable state machines that handle thread-level conversation history and integrate Vector Databases (such as pgvector, Qdrant, or Pinecone) to implement semantic memory via advanced Retrieval-Augmented Generation (RAG).
How do you secure agents against malicious prompts or jailbreaks?
We treat AI security as an infrastructure layer. We can implement strict input/output guardrails (such as NeMo Guardrails) to filter out prompt injections, safely handle system instructions, and enforce enterprise-level compliance guidelines.
