Agentic AI

Agents, in production — not in a demo.

ByteWave ships autonomous and human-in-the-loop agent systems that actually run business work. Our agents operate over your Snowflake and Databricks data, call your ServiceNow and Salesforce APIs, execute on your internal tools, and write back to your ERP. They run with observability, evaluation harnesses, guardrails, rate-limiting, kill switches and the audit trail your regulator will demand.

We choose the right framework per problem — LangGraph when you need stateful graphs and human-in-the-loop, CrewAI for role-based multi-agent teams, AutoGen for conversational collaboration, Semantic Kernel for .NET shops, the Model Context Protocol (MCP) for tool standardization, and Google’s A2A for cross-vendor interoperability. We are framework-agnostic by design.

What we deliver

• 01
  Multi-agent workflow design Agent topology (supervisor / swarm / hierarchical), role design, prompt contracts, memory strategy (short / long / episodic), tool registry design.
• 02
  Tool integration via MCP & function calling Model Context Protocol servers for Snowflake, Databricks, Salesforce, ServiceNow, SAP, custom APIs. OpenAPI → tool. SQL → tool. Vector search → tool.
• 03
  Production orchestration LangGraph Platform, Temporal, AWS Bedrock Agents, Azure AI Foundry, Vertex AI Agent Engine. Streaming, checkpointing, replay, durable execution.
• 04
  RAG & hybrid retrieval Snowflake Cortex Search, Databricks Vector Search, Pinecone, Weaviate, pgvector. Hybrid BM25 + dense + reranking, query rewriting, HyDE.
• 05
  Evaluation & guardrails LLM-as-judge, ground-truth evals, RAGAS, DeepEval, custom rubrics. NeMo Guardrails, Guardrails AI, content / PII / toxicity filters, jailbreak resistance.
• 06
  Observability & cost control LangSmith, Langfuse, Arize Phoenix, Helicone, Datadog LLM Observability. Token budgets, latency SLAs, eval-driven CI/CD, A/B shadow agents.
• 07
  Cross-vendor interop with A2A Google’s Agent-to-Agent protocol for inter-agent collaboration across vendors. Agent cards, discovery, capability negotiation.
• 08
  AI Act & EU compliance Risk-class mapping, human oversight, transparency logs, data lineage. ISO/IEC 42001 alignment, NIST AI RMF, model cards, bias audits.

Engagement model

Agent opportunity assessment (2 weeks) → reference architecture (1 week) → pilot sprint (4 weeks) → production rollout in waves with hyper-care. We hand you an agent that finance, compliance, and the regulator can all sign off on.

Outcomes you can measure

• Agent task completion rate 92%+ at p95 latency <5s.
• Cost per resolved task cut 65% vs human baseline.
• Hallucination rate <1.5% on ground-truth evals.
• Agent uptime 99.9% with durable execution.
• AI Act risk class documented and signed by CISO.

Stack & frameworks

Frameworks: LangGraph, CrewAI, AutoGen, Semantic Kernel, LlamaIndex, Haystack, Pydantic AI, smolagents, strands-agents, OpenAI Agents SDK, Google ADK.

Protocols: Model Context Protocol (MCP), Google’s A2A, OpenAI Function Calling, Anthropic Tool Use.

Models: OpenAI o-series, Anthropic Claude 4.x, Google Gemini 2.5, Mistral, Llama 4, Snowflake Cortex AI, Databricks Mosaic AI, AWS Bedrock, Azure OpenAI.

Vector DBs & retrieval: Snowflake Cortex Search, Databricks Vector Search, Pinecone, Weaviate, Qdrant, pgvector, Elasticsearch, Vespa.