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Production Agent Networks

Autonomous Multi-Agent Systems

Replace manual business processes with coordinated networks of specialized AI agents that plan, retrieve, execute, verify, and escalate through production controls.

Explore How We Engage See What We Build
Orchestration Specialized agents routed by workflow intent
RAG Hybrid retrieval with reranking and clean context
Guardrails Human approval gates for sensitive operations
Audit Trails Prompt, payload, model, and action traceability

Single prompt wrappers break the moment business logic gets conditional, stateful, or high-stakes. Production agents need orchestration, tool contracts, memory boundaries, approval gates, and telemetry.

ViaCatalyst builds agentic workflow engineering systems for finance, platform operations, data operations, customer workflows, and internal productivity platforms.

Outcomes

What this service is designed to improve.

Autonomous digital labor for multi-step operational workflows

LangGraph-style orchestration with state, retries, routing, and checkpoints

Human-in-the-loop gates for approvals, exceptions, and sensitive actions

Core capabilities

Focused capabilities.

Graph-Based Orchestration

We model workflows as explicit graphs with nodes, state transitions, failure paths, and verification checkpoints.

  • Planner, researcher, executor, evaluator, and escalation agent patterns
  • Durable workflow state for long-running business processes
  • Conditional routing, retries, fallback paths, and timeout handling

Tool and System Integration

Agents become useful when they can act safely inside the systems your teams already run.

  • Typed tool contracts for CRMs, ERPs, internal APIs, ticketing, billing, and data platforms
  • Sandboxed execution for generated code, calculations, file handling, and data transforms
  • Approval workflows for writes, financial operations, notifications, and external side effects

Operational Control Plane

We expose how agents decide, what they touched, and why an action was accepted or blocked.

  • Run logs across prompts, payloads, tool calls, model choices, and final outputs
  • Operator dashboards for queue state, exceptions, latency, and cost
  • Replayable test cases for regression checks before releasing workflow changes

Process

How we deliver.

01

Map the target workflow, decision points, systems, and risk boundaries

02

Design the agent graph, tools, state model, memory, and approval gates

03

Build a production-grade prototype with real models. We use deterministic validation gates and sandboxed execution environment testing before production deployment.

04

Deploy observability, evals, rollback paths, and operator workflows

Technology

Agent orchestration and runtime infrastructure.

LangGraph

OpenAI API

Anthropic Claude

LlamaIndex

CrewAI

Temporal

FastAPI

PostgreSQL

Redis

Kafka

OpenTelemetry

PostHog

Operational impact

Representative benchmark.

Mapped a finance planning workflow where analysts manually moved balance sheet assumptions across documents, approvals, and projections.

Defined an agent network that separates ingestion, projection, variance analysis, and human approval into auditable stages.

Related case patterns

Representative work.

Enterprise Knowledge RAG With Access Control

A permission-aware RAG layer for policies, contracts, product documentation, support history, and internal knowledge without crossing access boundaries.

Enterprise Knowledge Systems

B2B Platform AI Feature Integration

An AI capability layer for a live B2B platform with tenant-aware retrieval, assisted workflows, release gates, and product telemetry.

B2B Platforms

Agentic Operations Readiness

A readiness and architecture program for turning a manual internal workflow into governed agent execution with approvals and observability.

AI Operations

AI Observability and Evaluation Control Plane

An enterprise AI control plane for evaluation, tracing, release gates, model governance, cost visibility, and incident review.

AI Governance

Intelligent Document Processing for Compliance Review

An AI-assisted document workflow for classification, extraction, policy checks, exception routing, reviewer queues, and audit-ready decisions.

Regulated Operations
Can you work inside our existing cloud and security model?

Yes. We design around your current identity, network, data, CI/CD, and approval boundaries, then recommend only the changes needed to make the AI system production-ready.

Do you use public models with proprietary data?

We can use commercial LLM APIs, private endpoints, or self-hosted models depending on risk profile. Proprietary data is isolated from public training paths and access is designed around least privilege.

Can we start with a short diagnostic before committing to build?

Yes. Most engagements begin with a Two-Week Architecture Audit that produces a capability map, risk register, implementation roadmap, and validation plan.

Project inquiry

Discuss Agent Networks

Tell us which process is slow, repetitive, or error-prone and we will identify where autonomous execution is useful and where deterministic gates are required.

Next step

Turn manual workflows into governed agent networks.

Start with the Two-Week Architecture Audit so data access, workflow risk, validation, and operating needs are clear before build work expands.

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