Custom LLM layers on Salesforce — account intelligence, case summarization, and agent assist — with governor-limit-aware design and enterprise SSO.
Sales Cloud · Service Cloud · Apex · SSO · Audit logs
30 minutes · Senior engineer · No commitment
Production patterns that respect governor limits and compliance.
Auto-summarize long case threads for agents and generate customer-ready replies for approval.
Pre-call briefs from opportunities, activities, and external enrichment — surfaced in Lightning.
LLM-assisted scoring explanations your reps trust — not black-box numbers.
Invocable actions and platform events — AI fits your existing automation, not parallel silos.
Azure OpenAI or VPC-hosted models for data residency requirements.
Every inference logged with user, record ID, and prompt hash for review.
Where custom integration beats out-of-box Einstein.
Reduce handle time with suggested replies grounded in case history and knowledge articles.
AEs walk into calls with AI-generated account briefs updated nightly.
Authenticated customers query order and contract status from Experience Cloud.
Natural-language reports and anomaly flags pushed to Slack from Salesforce data.
Teams evaluating salesforce ai integration typically hit these blockers before finding a reliable partner.
Sandbox bots work until real CRM data, permissions, and rate limits appear.
Users get stuck in loops when the AI can't answer — churn follows.
Customer data sent to LLMs without redaction creates compliance risk.
Token spend spikes without monitoring or per-conversation caps.
150+ products shipped · US/UK/AU clients · Engineer-led delivery with QA sign-off.
We design for monitoring, escalation, and maintainability — not demo-day screenshots.
Laravel, React, Node, Flutter, n8n, and LLM integrations from one accountable team.
KPIs defined upfront — deflection rate, lead speed, defect escape, or time-to-market.
Fixed milestones with weekly demos so scope surprises don't appear at invoice time.
Typical salesforce ai integration timeline from API audit to production bot.
Stack chosen for your constraints — we don't force a template that fights your team's skills or compliance needs.
Scoped API keys and service accounts — never full admin unless required and approved.
PII redaction, audit logs, and NDAs before production credentials.
“What a 70-engineer team could not deliver, a small senior team at GreeLogix shipped. The app went from stuck to live across mobile, web, and backend.”
At-a-glance scope, pricing tiers, delivery timelines, engineering tradeoffs, and decision criteria for technical founders and product leaders.
Salesforce AI integration services design and implement custom large-language-model capabilities on your Salesforce org — case assist, account intelligence, and customer-facing bots — using Apex, Flow, and secure API patterns appropriate for enterprise compliance.
GreeLogix pricing tiers: Integration Sprint: $3,500 – $8,500 — Single-tool AI connection with staging validation and handoff docs. Production Integration: $8,500 – $22,000 — Multi-flow integration with CRM writes, escalation, and monitoring. Managed AI Ops: $4,500 – $12,000/mo — Ongoing tuning, model updates, and incident response for live integrations.
Single integration: 2–4 weeks. Multi-system: 4–8 weeks. Managed ops: monthly retainer. Phases: Discovery & API audit (Days 1–5); Build & guardrails (Weeks 2–4); QA & launch (Week 4–5); Tune (optional) (Month 2+).
Compare delivery models, cost profiles, and engineering tradeoffs before committing resources.
| Option / Approach | Best When | Primary Tradeoff / Risk | Recommended Fit |
|---|---|---|---|
| In-house hire | 12+ month roadmap with budget for recruiting and management | 3–6 month hiring cycle, high recruitment fees, and fixed long-term payroll overhead regardless of development volume. | Companies with dedicated HR pods |
| Offshore body shop | Well-defined tasks with internal tech lead and QA | High enterprise overhead markup, tiered account management layers, and slower communication turnarounds. | Large enterprise discretionary budgets |
| DIY no-code tools | Simple workflows under 500 monthly actions with no compliance needs | Scalability bottlenecks, vendor lock-in, architectural rigidity, and substantial technical debt before handling production traffic. | Early validation & UI experiments |
| GreeLogix Pod | Accountable production delivery with senior engineers, weekly demos, and fixed milestone velocity. | Requires active product owner for weekly sprint reviews and scope alignment. | Production & Scaling (Recommended) |
Talk to a senior engineer — scope, timeline, and cost range in one 30-minute call. No sales script.
Answers to the buyer questions we hear most before a project starts.
Often complementary. We build custom flows where Einstein lacks flexibility, multi-model support, or cross-system context.
Async processing, bulk-safe callouts, caching, and queue-based inference — designed with your Salesforce architect.
Yes. Azure OpenAI with private networking is our default for regulated clients.
Yes. We integrate alongside your SI for CRM config while owning the AI layer.
Map goals, stack, timeline, and success metrics.
Fixed milestones, pricing, and delivery plan.
Iterative delivery with staging reviews each week.
Production deploy, docs, and optional retainer.
Share your org edition, clouds in use, and top use case — we'll propose a secure architecture.
From chatbots and voice agents to workflow automation — pick the capability that matches your roadmap.
Case studies, guides, and free tools from the same engineering team.
Production-grade connections — not demo scripts that break under real CRM data.
Map APIs, auth models, rate limits, and which fields can safely feed an LLM.
Define user intents, escalation triggers, and write-back rules to your system of record.
Implement prompts, tool calls, PII filters, and fallback paths when the model is uncertain.
Test with realistic records, edge cases, and failure modes before production keys.
Deploy with logging, cost caps, and a runbook for human takeover.
Tangible artifacts your engineering and product teams can act on — not vague pass/fail notes.
Transparent ranges based on app complexity, platform count, and engagement depth. Final quotes follow a scoping call.
$3,500 – $8,500
Single-tool AI connection with staging validation and handoff docs.
$8,500 – $22,000
Multi-flow integration with CRM writes, escalation, and monitoring.
$4,500 – $12,000/mo
Ongoing tuning, model updates, and incident response for live integrations.
Prices in USD. Retainers and multi-platform engagements quoted after scope review. See agency pricing or explore QA as a Service for ongoing coverage.
Connect GPT-4, Claude, and automation to the tools your business already runs.
Browse the full ai integrations cluster from our AI Integration Services.
Scope, timeline, and cost range — no sales deck. Or start with the free readiness quiz if you are still evaluating your stack.
You'll talk to Abuzer — the senior engineer who'll scope your build
Founder & Senior Engineer · Response within 4 business hours
Book a Free 30-Min CallResponse within 4 business hours · No commitment on first call