An Agentforce consulting partner for AI agents that do real work

Our Salesforce AI consulting practice covers the full arc — Agentforce implementation services for the first pilot, agent design and guardrails at scale, and Agentforce managed services for the tuning that never stops.

Agentforce is Salesforce's platform for autonomous AI agents — software workers that plan and execute tasks rather than merely suggesting text. Agents run on the Atlas Reasoning Engine (plan → evaluate → refine), are grounded in your Salesforce and Data 360 data, act only through explicitly granted actions and permissions, and escalate to humans with full context when they shouldn't proceed. Salesforce reports 66% of service organizations now run AI agents, with 70% of adopters seeing measurable value within 60 days — and, at Reddit, 46% case deflection with response times falling from 8.9 to 1.4 minutes.

The trust story has three layers, often conflated: platform security (agents can't see or touch what their user context can't), the Trust Layer (masking, zero-retention model handling, toxicity detection, audit trails), and your guardrail design — topics, instructions, and deterministic paths for regulated steps. The first two ship with the platform. The third is where implementations succeed or fail, and it's the one you're actually buying from a partner.

Most AI rollouts fail at adoption, not capability. The highest-leverage design decision in an agent program is putting agents where work already happens.

The same Agent Builder produces both. The difference is who the agent talks to and how much autonomy it has earned.

Salesforce doesn’t force one integration style, and most enterprise rollouts end up using all three — chosen per use case, not by habit.

In practice: a customer asks a service agent “where’s my order?”; the agent checks the order system over MCP, finds a shortfall, delegates rerouting to an ops agent over A2A, and replies with the new ETA — five systems, one conversation, and only a save-call at the end needs a human:

Integration architecture is its own discipline; ours lives at Salesforce integration services.

Source: publicly published Salesforce Agentforce customer stories. Results are those customers’ reported outcomes, not a promise of yours.

The four-week promise in the ads assumes clean data and existing integrations. What actually drives duration:

Where the time actually goes: platform and data readiness (data cleanup is the single most common blocker), agent configuration and prompt engineering, integration build-out (weeks per system — less with MCP than custom API), adversarial testing and guardrails, and adoption. Ranges synthesized from publicly reported Agentforce implementation experience across SI partners; your timeline depends on data readiness and integration scope.

What to build first: look for processes that are high-volume (the win is visible fast), rule-based with exceptions (structured enough for an agent, varied enough to matter), data-intensive (synthesis is the real bottleneck), and handoff-heavy (coordination is the friction). Case triage and document processing sit squarely in that quadrant; a full contact-center replacement does not — and we’ll tell you so.

1. Weeks 1–2 — See. The Horus Eye evidence baseline, use cases ranked by evidence, and one chosen — narrow, measurable, high-volume. Our transformation loop governs every phase.
2. Weeks 3–6 — Architect & build. Grounding, permissions, guardrails; deterministic paths for regulated steps; the agent built and adversarially tested — hostile inputs, edge cases, prompt attacks — before any customer meets it.
3. Weeks 7–10 — Launch & measure. Production with health monitoring: resolution rate, escalation quality, CSAT, cost per interaction against the baseline.
4. Weeks 11–13 — Prove & plan. Measured results against the business case, and an evidence-based scale plan — or an honest recommendation not to scale. Both outcomes are wins; only one is common at other firms.

Certified Agentforce Specialists (earned at Dreamforce 2025), Data Cloud and Revenue Cloud certified, delivering on a platform we've implemented since 2019. Pricing: fixed-price pilots; consumption modeling included so finance sees the cost curve before signing. Run your own numbers in the ROI calculator.