Deployed LLM agents and workflow orchestration across CRM, ERP, and documents — with guardrails, audit trails, and human review where decisions matter ai automation.
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Enterprise professional services firm partnered with Spectrum to address operational and technology gaps in enterprise. Operations teams spent hours moving data between CRM, ERP, and shared drives. Ad-hoc ChatGPT use created compliance risk with no audit trail or consistent prompts. Spectrum applied a phased delivery model — 12-week pilot · 6-month scale-out — aligning stakeholders, compliance needs, and production cadence. Since 2016, Spectrum has delivered similar programs with managed teams and fixed-cost options.
Operations teams spent hours moving data between CRM, ERP, and shared drives. Ad-hoc ChatGPT use created compliance risk with no audit trail or consistent prompts.
Teams used public LLM tools without logging, guardrails, or approved data boundaries — creating compliance exposure.
CRM, ERP, and document workflows required hours of copy-paste and reconciliation between systems.
Leadership could not demonstrate who prompted what, or which data left the approved perimeter.
Prior experiments never reached production because integration and governance were afterthoughts.
The firm did not need another chatbot pilot — it needed agents that could touch CRM and ERP without bypassing compliance. We shipped production workflows in ninety days by pairing tool boundaries with retrieval over approved content, and by making auditability a first-class requirement rather than a post-launch patch.
Each agent is bound to explicit tools: read approved knowledge bases, draft customer-facing text, prepare CRM updates — never an open-ended “do whatever” prompt. Retrieval runs against indexed policy, product, and contract libraries with tenant isolation so one division cannot see another’s HR content. Structured actions call existing REST APIs with idempotent writes and backoff when downstream systems throttle. Operations sees a queue of proposed actions, not a black box that already committed changes.
Low-risk lookups run straight through; anything that changes pricing, contract terms, or financial fields stops for reviewer approval. Reviewers see the source passages the model used, the proposed payload, and a diff against the current CRM record. SLAs and escalation paths mirror how legal already handled exceptions — we did not invent a parallel process. Pilot teams in two divisions signed off on gate rules before wider rollout.
Every model call, tool invocation, and user correction logs with tenant, role, and correlation ID. Security can answer who prompted what and which document versions were in context — the question that blocked earlier experiments. Dashboards track latency, token cost, and exception rates so platform owners can cap spend and spot drift. Retention policies align with existing records management rather than inventing a separate silo.
We resisted the big-bang launch. Two business units ran live agents for six weeks with weekly releases and a shared war-room channel for misfires. Playbooks cover rollback, prompt version pinning, and how to disable a single tool without taking down the runtime. Scale-out added business units only after audit samples passed internal compliance review — not when the demo looked good.
Manual work reduced
Days to production
Audited AI actions
Agents sit behind policy-enforced tool gateways with retrieval over approved corpora — every write to CRM or ERP is optional, logged, and reviewable.
Orchestration hosts tool-bound agents with structured outputs, token budgets, and per-tenant configuration. Prompt and tool versions pin per release so security can reproduce behavior during investigations.
Indexed policy, product, and contract libraries feed retrieval with division-level isolation. Embeddings refresh on a schedule tied to document approvals — not on every user upload.
REST connectors into CRM and ERP use idempotent writes, exponential backoff, and dead-letter queues for throttled downstream systems. Read paths are cached where safe; write paths always pass human gates when risk class is high.
PII redaction, retention policies, and immutable logs cover model calls, tool invocations, and reviewer decisions. Dashboards show cost, latency, and exception rates per business unit.
Operators replay failed steps, disable a single tool without stopping the runtime, and export audit samples for compliance sampling. Rollback playbooks tie to weekly release tags.
Spectrum addressed bottlenecks and compliance needs while keeping delivery incremental and measurable.
Production agents with compliance-friendly audit trails.
Material reduction in manual document and CRM tasks.
Clear metrics on adoption, cost, and risk.
Governed agents now handle high-volume CRM and document work with full audit trails — shadow AI use dropped in pilot divisions.
Manual work reduced
Days to production
Audited AI actions
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Typical engagement · 12-week pilot · 6-month scale-out
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