BigStep helps SaaS and enterprise teams build scalable AI systems using LangChain, LangGraph, AI agents, and enterprise workflow orchestration.
Four engineering disciplines, one delivery team — scoped for the realities of enterprise environments.
Autonomous and semi-autonomous AI systems designed for workflow automation, reasoning, and operational execution.
Retrieval systems, tool orchestration, memory handling, and modular AI application development.
Stateful workflow orchestration with approvals, retry logic, and multi-agent execution flows.
AI integrations across APIs, CRMs, ERP systems, internal tools, and operational platforms.
Prototypes work. Production breaks. These are the eight failure modes we see most often when teams move from demo to deployment.
Agent loops drift, tool calls fail silently, and there's no recovery path.
Outputs look fluent but invent data — fatal in regulated workflows.
Brittle glue code between AI and CRM, ERP, and internal APIs.
No approval gates, no audit trail, no policy alignment.
Notebook-grade pipelines collapse under real traffic and concurrency.
AI sits on the side, not embedded in the operating workflow.
No traces, no evals, no way to know what went wrong — or right.
Outputs aren't validated or typed — downstream systems can't consume them.
A production-grade architecture distilled from real BigStep deployments — engineered for reliability, observability, and enterprise integration.
Six workflow patterns we’ve shipped into production environments — engineered for measurable operational impact.
Triage, deflect, and resolve customer requests with grounded agents — escalating intelligently when human judgment is required.
Accelerate CRM workflows, personalized outbound, and pipeline operations with AI agents grounded in your win-loss data.
Automate repetitive internal processes across HRIS, finance, and ops with structured AI workflows and HITL checkpoints.
Unified, governed knowledge surfaces — grounded in your data, role-aware, and aligned to internal policy. HIPAA-aligned and GDPR-aware where regulated content is involved.
Long-running operational workflows — orchestrated, observable, and resilient to model and tool failures.
Cross-system retrieval grounded in vector and structured stores — with permissions, lineage, and explainability.
A selection of recent BigStep engagements — anonymized, focused on operational impact.
A production agent layer with HITL approvals, embedded into the operating workflow — reducing repetitive support load and accelerating triage consistency.
CRM-integrated AI agents for outbound personalization and pipeline ops — orchestrated through LangGraph workflows with audit trails.
Structured AI orchestration for internal back-office workflows — with role-aware retrieval, policy guardrails, and full LangSmith traces.
Grounded retrieval across regulated content with role-based access — improving time-to-answer without compromising governance. Designed with HIPAA-aligned processes, GDPR-aware data flows, and strict PII minimization.
We’ve shipped production systems on both — and we know which problem each one is right for.
Every BigStep production graph is instrumented with LangSmith traces and regression evals — so buyers can inspect runs in a 30-minute technical review.
Full LangSmith trace history across graphs, agents, tool calls, and retries — ready to share with stakeholders.
CI-integrated regression testing and guardrail checks — fail builds when quality, latency, or cost regress.
Versioned prompts with deployment tagging — roll forward and back safely without redeploying the app.
A dedicated cost-optimization layer is built into every BigStep AI System — keeping unit economics defensible at scale.
Reuse previous answers for semantically equivalent queries — cutting tokens, latency, and spend on repeated traffic.
Simple queries to small/cheap models. Complex or critical flows to frontier models. Routed automatically — measured continuously.
Non-latency-sensitive workloads — report generation, offline enrichment, backfills — moved to batch APIs and scheduled windows.
A structured five-phase delivery model — predictable cadence, observable milestones, real production hand-off.
Map workflows, find friction, score impact × feasibility.
Reference architecture, integration points, governance plan.
Agents, LangGraph workflows, retrieval & tool layer built.
CRM/ERP/API wiring, eval harness, security & UAT.
Observability, evals, model upgrades, capacity ops.
Talk to BigStep about AI agents, LangChain systems, LangGraph workflows, and enterprise AI automation.
Talk to BigStep AI Team