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Salesforce + AI engineering

Agentforce development services

AI agents inside Salesforce that do real work, built by a team that ships both Salesforce and production AI, and will tell you honestly which one you need.

Get an Agentforce readiness assessment

What is Agentforce development?

Agentforce is Salesforce's platform for AI agents that act inside your CRM, reading records, following your business rules, and taking actions like creating cases or updating opportunities, with org permissions enforced. Codiot builds Agentforce agents end to end: the agent design, the custom actions behind them, the data grounding they depend on, and the testing that proves they behave before your customers meet them.

Agentforce or a custom agent? We build both, so we'll tell you straight.

Agentforce wins when the work lives in Salesforce: CRM-context answers, record actions, org permissions, and speed to deploy matter more than flexibility. A custom agent wins when the workflow spans systems Salesforce doesn't own, when you need model choice and eval depth beyond the platform's rails, or when consumption pricing doesn't survive your volume math. Plenty of real answers are both: Agentforce at the CRM edge, a custom agent behind it. We build custom agents and Agentforce, so the recommendation follows your workflow, not our bench.

Capabilities

What we build.

Readiness and data grounding

An agent is only as good as the records and knowledge it stands on; we fix the data layer before the demo, not after the complaints.

Agent design and topic architecture

Instructions, topics, and escalation paths designed like software, not written like marketing copy.

Custom actions

The Apex, Flows, and API integrations that let an agent actually do things: quote, schedule, update, refund, escalate.

Evals and testing

Scripted and adversarial test suites that measure whether the agent answers correctly, refuses correctly, and escalates correctly, run before and after every change.

Guardrails and governance

Permission scoping, Einstein Trust Layer configuration, audit trails, and the boundaries that keep an autonomous agent inside policy.

Rollout and cost control

Phased deployment, monitoring, and usage modeling so consumption-based pricing doesn't surprise your CFO.

How it works

How it works with Codiot.

  1. Readiness assessment

    Your data, your workflows, your volume economics, and a plain answer on whether Agentforce is the right tool.

  2. One agent, in production

    The highest-value workflow first, with actions, evals, and guardrails, live to a limited audience.

  3. Expand on evidence

    Deflection, resolution, and cost-per-conversation numbers decide what the agent learns next.

Why Codiot

Stack we use, and why teams choose us.

AgentforceApexSalesforce FlowEinstein Trust LayerData CloudLightning Web Components
  • ·We build both Agentforce and custom AI agents, so the recommendation follows your workflow, not our bench.
  • ·Evals and guardrails engineered in from the start, not bolted on after an incident.
  • ·We fix the data grounding before the demo, because most stalled pilots are data problems in an AI costume.
  • ·Consumption pricing modeled against your real volumes, so the bill doesn't surprise your CFO.
Is this right for you?

When it fits, and when it doesn't.

Signs you need this

  • ·Service or sales workflows are drowning in volume.
  • ·An Agentforce license is already paid for and sitting idle.
  • ·A pilot answers questions but can't take actions.
  • ·There's pressure to do AI, with governance requirements attached.

What's included

  • ·Readiness assessment, agent and action engineering.
  • ·Eval suites and guardrail configuration.
  • ·Rollout monitoring and cost modeling.

What's not

  • ·Agentforce licensing and consumption fees, which you hold with Salesforce directly.
  • ·Your policy decisions: we encode the escalation rules, you set them.

When this isn't the right fit

  • ·The workflow lives mostly outside Salesforce, where a custom agent fits better, and we'll say so.
  • ·Your data isn't ready and you want the demo anyway.
  • ·Volumes are so low that a well-built Flow would do.
FAQ

Common questions, answered plainly.

How much does Agentforce cost to run?
Two costs to separate: Salesforce's own pricing (consumption-based, Flex Credits per agent action, on top of platform licenses; it changes, so we model it against your real volumes during the assessment rather than quoting a stale number) and the build. We scope the build against the actions and integrations your agent needs rather than a headline figure.
Agentforce vs building a custom AI agent, which is cheaper?
At low volume, Agentforce is usually faster and cheaper to stand up. At high volume, consumption pricing can cross over the cost of a custom build within a year. We'll do that math with you before recommending either, because we build both and don't need the answer to come out a particular way.
What does Agentforce need from our data before it's useful?
Grounded knowledge (clean articles, structured records) and reliable field data for actions. Most stalled pilots are data problems wearing an AI costume; the assessment tells you honestly how much cleanup stands between you and a useful agent.
How do you stop the agent from saying something wrong?
Engineering, not hope: scoped permissions, Trust Layer configuration, topic boundaries, and eval suites that test wrong-answer and refusal behaviour before every release. Agents that ship without evals are incidents on a delay.
How fast can a first agent go live?
A first production agent with real actions typically ships in 6-10 weeks from assessment, assuming the data layer doesn't need major surgery.
Start

Let's talk about Agentforce development.

Tell us what you're building. We'll reply within two business days with an honest take on scope, timeline, and cost.

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