ConvergeSol accelerates the entire Salesforce build—spanning customization, complex integrations, deep automation, and intelligent agents. Traditional components like UI, Apex code, record-triggered flows, named credentials, data model architectures, Experience Cloud portals, Agentforce, and vPilot no longer need to stall inside lengthy multi-week sprint cycles. By running this workload directly through Cursor, Claude Code, and the modern Salesforce toolchain, full-stack CRM capabilities are delivered in rapid, production-ready slices rather than prolonged sprint theater.
We handle the technical execution while maintaining human rigor over requirements, security, test coverage, and production acceptance. You retain full client ownership and strategic oversight. Whether the optimal solution calls for native Salesforce engineering or a dedicated hosted application when Salesforce is the wrong operational fit, we focus strictly on shipping reliable, high-velocity outcomes using our integrated stack across Cursor, Claude Code, Agentforce, vPilot, Salesforce CLI, and Jira.
Speed & Scope
Traditional SIs vs. Human + AI
How We Ship: SI Hours vs. AI-Driven Execution
What actually used to pad the SOWThis is not an LWC demo. It is customization, integration, automation, data, portals, and in-org AI — the work a mid-market Salesforce program is made of. Generation time assumes a Ready Jira ticket. Human time is design, review, and acceptance. We will not skip it.
Custom UI
30–40 hours
~15 min
Lightning Web Components, record pages, screens a rep will actually use.
Apex & automation
16–24 hours
20–40 min
Triggers, services, tests, bulk and sharing. Flow when Flow is enough.
Integrations
1–3 days
Hours
Named credentials, REST, accounting/ERP stubs, errors with an owner.
Data model
Days of clicks
Same day
Objects, fields, FLS, list views, compact layouts — as metadata in git.
Flows & approvals
8–12 hours
15–30 min
Record-triggered and screen flows that do not fight the ones already there.
Portals
Weeks
Days
Experience Cloud when it fits. Hosted portal when it is cheaper and clearer.
Agentforce
Program quarter
Days
Topics, actions, Prompt Builder, grounding. Only after data and security pass.
vPilot
Wait for SKUs
This week
In-org copilot: summaries, agentic Flow/Apex/LWC — without an Agentforce license tax.
How we actually build
The toolchain we use every week — not a slide of logos.Cursor and Claude Code write the code. Agentforce and vPilot are how intelligence shows up in the org. Salesforce CLI, git, and Jira are how it stays shippable. A consultant still signs production.
Cursor
Repo-native IDE. Reads the Jira ticket, writes LWC, Apex, tests, and metadata against the sandbox branch.
Claude Code
Long-running agent on the same repo: multi-file refactors, integration stubs, test packs, comments on incomplete tickets.
Agentforce
Native agents, Prompt Builder, topics and actions. We implement it when the CRM is used and the data can ground it — not as a leftover SKU.
vPilot
Agentic patterns inside Salesforce without waiting for Agentforce licenses: record/email summaries, Flow + Apex + LWC orchestration to the LLM you choose.
Salesforce CLI
sf retrieve/deploy, Dev Hub, scratch orgs, named credentials. AI never clicks production. Promotion is a human move.
Jest + Apex tests
Generated with the slice, reviewed by a human. Coverage and edge cases are part of Accepted — not “we’ll test in UAT.”
Jira
One project per client. Requirement, estimate, design, build, accepted. The board is the commercial record.
Git
Every generate is a pull request. Metadata lives in the repo. Chat transcripts are not the source of truth.
What we are good at
Human judgment plus a bench of AI tools — not one chatbot in a demo.The consultant knows sharing, governor limits, a messy Account hierarchy, and what “done” means for a dispatcher. The tools never get tired of boilerplate. That pairing is the product.
Human-Led Strategy
- Requirement articulation — actor, object, exception, done-state
- Estimate from those requirements: UI, integration, automation, agent
- Design: data model, security, UX, integration contract, grounding
- Review: tests, FLS, bulk, mapping, “does this belong in Salesforce?”
- UAT, production promotion, and the commercial outcome
AI-Driven Execution
- Cursor + Claude Code: LWC, Apex, flows, tests, metadata, integration stubs
- Agentforce: topics, actions, Prompt Builder — when the org can hold it
- vPilot: in-org copilot and agentic patterns without the license wait
- sf CLI + git: retrieve, deploy, scratch orgs, pull requests
- Jira: comment on gaps, estimate, move to Dev in Progress only when Ready
Org Assessment
Is Salesforce the system of work, or an unused license stack with an AI add-on?The current problem is not “they need more customization.” It is idle seats, Excel as the real CRM, overlapping flows, everyone System Admin, and Agentforce or Einstein sitting on data nobody trusts. We inspect, score, and recommend whether to keep, simplify, use a hybrid approach, or use a hosted app. Then the method has something honest to build.
Access
Read-only or sandbox, user list, installed packages, 90 days of login / storage / API usage, and a list of paid AI or Einstein SKUs that are not in daily use.
Inspect
Licenses, objects, automation collisions, security, adoption, integrations, technical debt, and whether the real process even belongs in CRM. Same checklist every time.
Recommend
A path plus the first Ready tickets. Optimize Salesforce, right-size it, split work with a custom app, or replace the process app and host it. Commercial model comes after the path, not before.
Assessment Areas
Key areas we evaluate to identify risks, gaps, and 2026 failure modes.| Area | Healthy signal | Warning signal (current) |
|---|---|---|
| License use | Active users match paid seats; edition matches the process | Seats unused; Enterprise or extra clouds bought for a 12-person team |
| Adoption | Daily login for core roles; pipeline and cases actually live in Salesforce | CRM is a filing cabinet; Excel, email, or a vertical SaaS is the real system |
| Data | Duplicates controlled; required fields used; reports trusted | Empty required fields, duplicate accounts — this is what kills Agentforce and any “AI on CRM” story |
| Automation | Documented flows; few overlapping rules | Legacy workflow + process builder + flows fighting each other; AI will happily add a fourth |
| Security | Least-privilege profiles/permission sets, MFA, sensible sharing | Everyone is System Admin; guest or sharing holes — we will not generate Apex onto that |
| Customization | Custom objects earn their keep; LWC/Apex has tests | Unused managed packages, dead objects, untested Apex; a customization and integration backlog still quoted like 2019 typing |
| Integrations | Named systems, error handling, an owner | Brittle middleware, silent failures, nobody knows the mapping |
| AI / Agentforce / vPilot fit | Clean objects, used CRM, a real question the agent should answer; Agentforce if licensed and grounded, vPilot if they need in-org AI without that SKU | AI SKU sold, no grounding data, no owner, no use case beyond the pitch deck |
| Process fit | Lead-to-cash or service path matches how the company works | The real workflow is scheduling, jobs, inventory, or a portal Salesforce is stretching to hold |
What Our Clients Say
At ConvergeSol, our mission is to guide organizations through complex technology choices. We partner with our clients to design, build, and optimize solutions that support growth, efficiency, and long-term success.
We were spending too much time on status questions, warranty checks, and finding qualified technicians. ConvergeSol helped streamline our service operations with Agentforce, enabling faster customer answers, quicker technician selection, and fewer manual lookups and rework.
Industrial Equipment Manufacturer
Recruiters were spending valuable time searching for qualified tax candidates and keeping up with constant status requests. To simplify the process, ConvergeSol introduced Agentforce AI to identify the best-fit candidates, track progress 24/7, and give hiring managers real-time visibility. The result is faster sourcing, fewer emails, and a smoother hiring experience.
Specialist Recruitment Firm
ConvergeSol helped us bring fragmented data together with Financial Services Cloud and streamline our retail and commercial banking operations. We improved customer service, reduced manual data management time by 30%, increased retention by 15%, and created 40% more cross-selling opportunities.
Finance Firm
ConvergeSol helped us streamline volunteer management with Salesforce Nonprofit Cloud, making it easier to coordinate volunteers, manage programs, and track hours. We improved participant engagement, strengthened program delivery, and gained better visibility for data-driven decisions.
Non Profit
