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PerplexityGetGenerative.ai Updates: Platform Changelog 2026
This page records what is current across the GetGenerative.ai platform and services. It is maintained rather than published once, so the sections below reflect where things stand today rather than at launch.
Six agents cover discovery through post-go-live support
The platform is a workspace with six agents, each owning a stage of the implementation artifact chain.
Agent | What it produces | Stated effort saved |
|---|---|---|
Discovery | Roadmap, business case, scope, schedule and resourcing plan | Up to 70% on business case creation |
Metadata | As-is org blueprint, technical debt and drift, remediation roadmap | Up to 80% on org review and remediation |
Design | Low-level solution design, user stories, acceptance criteria, Jira project setup | Up to 70% on stories and solution design |
Build | Implementation workbooks, configuration and code, deployment to sandboxes | Up to 60% on configuration and coding |
Testing | Test strategy, test cases, test run management, defect tracking | Up to 50% on test cases and defect management |
Support | BAU and enhancement analysis, dependency and impact assessment, fixes | Up to 70% on post-go-live support |
Two properties separate this from a general assistant. Output deploys rather than returning as text, landing in Salesforce as configuration and code, in Jira as stories and project structure, and in GitHub for version control. And the Metadata Agent reads org configuration rather than records, which is what lets design recommendations account for what is already built.
Support Agent draws context from four sources including Salesforce MCP
The Support Agent understands an org before recommending a fix, using business process, code base, metadata, and Salesforce MCP for real-time org access and connected data.
The MCP connection is the one worth noting for anyone evaluating on security grounds, because org access runs under the platform’s own permission model rather than requiring an export.
Studio configures the GetGenerative.ai platform per firm
Studio is the configuration layer. It connects to Salesforce Headless 360 for enterprise-wide context, and covers four further areas: bring your own LLM, integrate your own data sources, adapt the methodology to your SDLC and governance, and customise templates for brand consistency.
The platform is frontier-model agnostic, tested across models from OpenAI, Google, Meta and Anthropic, and is built on Salesforce, Agentforce, AWS and LangChain.
Forward Deployed Engineer pods scale in three steps
Services are delivered by FDE pods rather than resource pyramids. Each pod is led by an engineer with a minimum of twelve years of Salesforce delivery experience, hands-on configuration and development background, and architecture and delivery ownership. The agents act as team members inside the pod across discover, analyse, design, build, test and deploy.
Engagement shape | Pods | Suits |
|---|---|---|
Focused implementation | 1 pod | Single-cloud implementations, remediation projects, focused enhancements |
Mid-size transformation | 2 to 3 pods | Multi-workstream programmes across sales, service, experience, data or automation |
Enterprise programme | Multiple pods | Large-scale, multi-cloud, multi-region or phased transformation |
More than 200 Salesforce projects delivered, with platform capability trained across more than thirty Salesforce clouds including core, industries, Data 360 and Agentforce. The delivery philosophy behind that structure is set out in the AI-led implementation pillar.
Managed services runs review, remediate and run
The stated aim is reducing Salesforce managed services cost by up to 80 percent, and the structure behind that claim is three agents mapped onto three phases.
The Metadata Agent reviews the org and produces the as-is view, identifying technical debt, architecture drift and remediation priorities. The Build Agent converts those priorities into workbooks, configuration changes, code updates and deployment-ready fixes. The Support Agent handles bugs, enhancements and BAU requests with triage, impact analysis, fix generation, documentation and testing, drawing context from business process, code base, metadata and Salesforce MCP.
The full cycle runs review, prioritise, remediate, resolve, validate and improve, with a Forward Deployed Engineer governing the decisions rather than a status report.
The entry point is a complimentary org review including a health check, a technical debt and risk assessment, a remediation roadmap, five support tickets fixed in one day, and thirty days of platform access.
A4X packages Agentforce activation at fixed price
Agentforce activation is productised rather than quoted, which is possible because the delivery method is standardised.
Package | Price | Kickoff to live | Suits |
|---|---|---|---|
Small | $5,000 USD | Around 14 days | Proving value on a single function, typically sales or service |
Medium | $10,000 USD | Around 4 weeks | Two or three adjacent functions |
Large | $20,000 USD | Around 6 to 8 weeks | Org-wide activation across the customer lifecycle |
Up to six live agents per engagement, selected from a catalogue of ten spanning sales, service, marketing, commerce, field service, HR and IT, each labelled by data source requirement and by credit intensity so the consumption implication is visible before selection. Scope is identical across packages; only agent count and depth per agent change.
Inclusions and exclusions are published rather than negotiated. Agent configuration, subagent definitions, standard and custom actions, Salesforce-native data access, sandbox testing, one production deployment and a knowledge transfer session are in. Apex development, new external integrations, new Data 360 ingestion, custom UI, data migration, Salesforce licensing and post go-live hypercare are out.
Delivery is co-sell with Salesforce ANZ, every engagement is led by a certified Salesforce engineer from discovery through handover with no offshore handoff, and the build uses Agent Script, Testing Center coverage and a configured Trust Layer.
Credits price usage at five dollars each
Tier | Price | Includes |
|---|---|---|
Free trial | $0 for 7 days | Full access to every agent, up to three deliverables, all premium models, no credit card |
Pro | $200 per month billed annually | Unlimited agent access, credit allowance, admin dashboard with usage stats, team members |
Enterprise | By arrangement | Custom implementation and integrations, Studio access, advanced security, bring your own data and LLM, templates, dedicated customer success |
Credits are the usage currency at $5 each, pooled at account level and shared across the team on both paid tiers, with volume discounts on add-on purchases. Deliverable creation and regeneration draw different amounts, so cost tracks output rather than seats. To see the agents against a live opportunity before committing, try every agent free for a week.
GetGenerative.ai holds SOC 2 and ISO certifications
Encryption in transit and at rest, independent security audits and penetration testing, role-based access controls with granular data-privacy settings, and compliance with SOC 2 and ISO standards. Certifications displayed include Salesforce Partner, ISO 22716:2007 and AICPA SOC.
Customer data is never used to train AI models, the platform’s own or any third party’s.
Integrations cover Salesforce for reading org metadata and deploying configuration and code, Jira for pushing user stories, acceptance criteria and project setup, GitHub for version control and code deployment, and additional project management and DevOps tools through custom integrations. The wider Salesforce partner ecosystem context matters here, since the consulting track moved to two tiers and twenty-eight competencies during 2026.
What is current across GetGenerative.ai, at a glance
Item | Detail |
|---|---|
Agents | Discovery, Metadata, Design, Build, Testing, Support |
Output destinations | Salesforce configuration and code, Jira, GitHub |
Real-time org access | Salesforce MCP, used by the Support Agent |
Configuration layer | Studio: Headless 360, LLM, data, methodology, templates |
Delivery unit | FDE pods, twelve years minimum, scaling one to many |
Agentforce packages | $5,000, $10,000 and $20,000 USD, fixed scope |
Managed services entry | Complimentary org review, five tickets fixed in a day |
Trial | Seven days, all agents, three deliverables, no card |
Credit value | $5 each, pooled across the account |
Training on customer data | None |
Maintainer note. Each future entry should carry a date, the area affected, and one sentence on what changed for a user. Three items to correct elsewhere on the site while updating this page: the implementation page states 25+ cloud mastery in its statistics band and 30+ Salesforce Clouds in its expertise section, so one page carries two different numbers for the same claim; the enterprise solution page still describes a five-agent model that predates the current six; and the sitemap indexes both a new-home-page and a pricing-old URL.
