Who We Help · Mid-Market
Agentic AI Implementation for Mid-Market Companies
Mid-market companies have the data volume and workflow complexity to benefit from multi-agent systems — but not the bureaucracy that slows enterprise rollouts. We design 8–12 week implementations that connect 4–8 systems, deploy governed agents with human-in-the-loop approval, and include continuous evaluation so performance improves after launch.
Where the friction lives
- ›Multiple SaaS tools that do not talk to each other, creating swivel-chair workflows
- ›Teams manually reconciling data between CRM, ERP, and support systems
- ›Growth outpaced operations — hiring more people just to keep up
- ›Pilot projects that prove the concept but never reach production
- ›Security and compliance requirements that consumer AI tools cannot meet
High-ROI use cases
Cross-system reconciliation agent
Monitors discrepancies between Salesforce, NetSuite, and support tickets; drafts the correction memo; routes to the right owner for approval.
80% of daily reconciliations automated
Demand-to-delivery agent
Senses pipeline changes, flags capacity constraints, proposes schedule adjustments, and drafts customer comms for operations approval.
20–30% faster order-to-delivery cycle
Policy & compliance watch agent
Tracks regulatory and internal policy changes, diffs against your control library, and drafts remediation tickets for legal review.
Days of policy lag → hours
Tier-1 support + escalation agent
Resolves order-status, billing, and onboarding queries across KB, CRM, and billing system. Escalates with full context, not a blank ticket.
40–60% Tier-1 deflection with full audit trail
How we help
Multi-system architecture
We map your current tool graph (CRM, ERP, ticketing, docs, warehouse) and design agents that read and write across them via MCP and secure API bridges.
Governance from day one
Every agent ships with human-in-the-loop gates, audit logging, and eval harnesses. Not bolted on later — designed in.
CI/CD for agent behavior
Prompt changes, tool additions, and model upgrades run through automated evaluation before production. Regression tests block bad deploys.
Team enablement
We train your engineers and operations leads to monitor, tune, and extend the agents. You build internal capability, not vendor dependency.
Expandable scope
Start with 2–3 workflows in the first implementation. Add new agents that share the same memory, governance, and evaluation layer.
Engagement model & pricing
Mid-market implementations run 8–12 weeks in two phases. Phase 1 (weeks 1–4): Architecture, data mapping, and governance design. Phase 2 (weeks 5–12): Agent build, system integration, evaluation harness, and production launch with team handoff. Typical range: $35K–$85K depending on system count and workflow complexity. Monthly operations retainers available post-launch.
What you get
- Multi-agent systems across 4–8 business systems
- Governance and human approval built in from day one
- CI/CD evaluation gates that prevent regressions
- Team training so you own the capability
- Modular expansion — new workflows plug into existing memory and guardrails
- Local Orange County team with on-site workshops available
Frequently asked questions
How is mid-market different from enterprise AI implementation?+
Mid-market moves faster. We skip the 6-month procurement and POC theater and go straight to a scoped pilot with real data. Governance is still rigorous, but the layers of committees and change-control boards are replaced by weekly working sessions with your operations lead and one executive sponsor.
What systems do you integrate with?+
Common mid-market stacks: Salesforce, HubSpot, NetSuite, SAP Business One, Zendesk, Slack, Google Workspace, Microsoft 365, Shopify, and custom databases. If it has an API or MCP server, we can connect it.
How do you handle security and compliance?+
Agents run in your environment or a dedicated VPC. We enforce ACL propagation, audit every action, and can align with SOC 2, HIPAA, or GDPR requirements depending on your industry. No data is used to train third-party models.
What does the 8–12 week timeline look like?+
Weeks 1–2: Triage and architecture. Weeks 3–4: Data connections and governance scaffold. Weeks 5–8: Agent build and internal testing. Weeks 9–10: Evaluation and hardening. Weeks 11–12: Production launch and team handoff. We run weekly sprint reviews with your team.
Can we start with one workflow and expand later?+
Yes. That is the recommended approach. The first workflow establishes the memory layer, governance model, and evaluation harness. Every subsequent workflow reuses that foundation, cutting the incremental cost and timeline by 40–60%.