Agent Architecture & Strategy
Define agent scope, capabilities, data access, action libraries, and escalation triggers — ensuring agents are built on a solid foundation that scales safely across departments and processes.
Services — Technology
AI & Agents
Development
Forsys is an early adopter and Agentforce implementation specialist — building autonomous AI agents that handle lead routing, case deflection, quote generation, contract review, and renewal management with no human intervention required.
The Agentforce Build Framework
From agent strategy to autonomous production agents
Forsys has deployed AI agents across 200+ Salesforce and Oracle engagements — we know how to build agents that actually work in production.
Forsys builds AI agents on Salesforce Agentforce, Oracle Digital Assistant, and custom LLM-based frameworks — covering the full agent lifecycle from strategy and architecture through development, testing, and production operation. We are early adopters of Agentforce Revenue Management and have deployed autonomous agents for lead management, service resolution, CPQ automation, and contract intelligence.
- Agentforce agent architecture and strategy
- Custom agent development with low-code and API tools
- Agent testing with AITest — Forsys's AI-powered QA platform
- Production deployment, monitoring, and agent optimization
The Agentforce Build Framework
01
Assess
Map automation opportunities and define agent scope, data requirements,
and success metrics
02
Design
Architect agent topology, action libraries, data connections, and
human-in-the-loop escalation patterns
03
Configure
Build agents using Agentforce low-code tools and custom Apex/APIs for
complex agent logic
04
Optimize
Monitor agent performance, refine prompts, retrain models, and expand
agent scope iteratively
Key Capabilities
Everything you need to build AI agents that work in production
Agentforce Build & Deploy
Native Agentforce agent development — configuring Einstein AI actions, Flows, custom Apex tools, and API integrations to build agents that execute across Sales, Service, Revenue, and Commerce clouds without human intervention.
Custom Agent Development
Build agents beyond the Agentforce toolkit — custom LLM integrations, Oracle AI agents, or multi-agent architectures — using Forsys's AI engineering team and proprietary accelerators.
Agent Monitoring & Optimization
Post-launch agent performance monitoring — tracking conversation completion rates, escalation volumes, accuracy metrics, and business KPIs — with Forsys's continuous improvement service for deployed agents.
Our Approach
From opportunity assessment to optimized production agents
A structured agent development engagement built from 200+ Salesforce and Oracle AI deployments.
Agent Opportunity Assessment
We map automation opportunities across your revenue stack — identifying which processes are best suited for AI agents based on volume, structure, and ROI potential.
- Process automation mapping
- Agent ROI scoring
- Data readiness assessment
- Agent scope definition
Agent Architecture Design
We design the agent topology — capabilities, data connections, action libraries, escalation patterns, and human oversight model — before development begins.
- Agent capability design
- Action library definition
- Data access architecture
- Human-in-the-loop design
Agent Configuration & Build
Using Agentforce low-code tools and custom API integrations, we build and configure agents — iterating in 2-week sprints with stakeholder demos and feedback.
- Agentforce configuration
- Custom Apex & API tools
- Data integration setup
- Sprint demos & iteration
AI Agent Testing (AITest)
Forsys's AITest platform runs comprehensive agent testing — covering functional accuracy, edge cases, adversarial prompts, and load scenarios — ensuring agents are safe and reliable before go-live.
- Functional accuracy testing
- Edge case & adversarial testing
- Performance & load testing
- UAT & safety review
Production Agent Deployment
Managed go-live with agent monitoring dashboards, user training, and a 90-day hypercare programme — ensuring agents deliver ROI from day one.
- Production deployment
- Agent monitoring setup
- User training & enablement
- Hypercare support
Continuous Agent Improvement
Post-launch agent optimization — prompt refinement, model updates, new action development, and scope expansion — driven by production performance data and business feedback.
- Performance analytics review
- Prompt & model refinement
- New action development
- Agent scope expansion
Business Outcomes
Measurable results from every agent deployment
Real outcomes from Forsys AI agent engagements across Salesforce and Oracle implementations.
4.8/5
CSAT across all Agentforce implementations
Forsys Salesforce Summit Partner
80%
Reduction in manual task handling by deployed agents
HiTech — Agentforce Sales
37%
Jump in win rate with AI-guided deal agents
Pharma Manufacturer — Agent Automation
3 wks
Average deployment time for standard Agentforce agents
SaaS — Agentforce Build
Client Success
AI agents that deliver measurable revenue impact
37% Win Rate Improvement with Agentforce Revenue Agents
A SaaS enterprise engaged Forsys to build Agentforce autonomous agents for their Salesforce Revenue Cloud. We deployed agents for AI-guided deal pricing, renewal management, and contract amendment — eliminating manual RevOps bottlenecks and improving win rates by 37% in the first two quarters post-launch.
- 37%
- Win rate improvement
- 80%
- Manual task reduction
- 3 wks
- Deployment time
FAQ
Frequently Asked Questions
-
What differentiates autonomous AI agents from traditional RPA workflow automation?
Unlike rigid RPA that relies on fixed, rule-based scripts, autonomous agents adapt to dynamic variables. Forsys develops agentic AI solutions that use real-time reasoning and LLMs to understand user intent, make context-aware decisions, and execute complex, unstructured task automation workflows without human intervention.
-
How does an AI readiness audit prevent deployment failures in enterprise workflows?
An audit identifies critical gaps in your data infrastructure, security, and process alignment before development begins. By conducting a thorough AI readiness audit, Forsys ensures your underlying enterprise data is clean and accessible, creating a stable foundation for autonomous agents to execute tasks accurately.
-
Can autonomous agents safely handle complex decision-making without human oversight?
Yes, within defined guardrails. Forsys designs an agentic AI strategy that utilizes strict prompt engineering, confidence-scoring algorithms, and secure API boundaries. This setup allows agents to automate high-volume tasks independently while smoothly routing edge cases to human teams using built-in escalation patterns.
-
How long does it take to deploy a custom Agentforce or Oracle AI agent?
While highly complex multi-agent ecosystems take longer, Forsys typically deploys standard autonomous agents into production in about three weeks. This accelerated timeline covers initial strategy alignment, low-code tool configuration, custom Apex or API integrations, and rigorous performance testing.
-
Which specific business processes are best suited for an agentic AI strategy?
The highest ROI comes from high-volume, data-heavy processes. Forsys specializes in deploying autonomous agents for lead routing, customer case deflection, complex quote generation, contract reviews, and subscription renewal management, effectively eliminating operational bottlenecks across your revenue and sales pipelines.
Ready to deploy AI agents that work autonomously?
Start with a free Agent Opportunity Assessment. We'll identify your top 5 agent use cases and a 90-day deployment roadmap.