soliantconsulting.com/salesforce

Yes. For a **Softr client portal**, I’d strongly recommend hiring someone who is specifically a **Softr Expert**, rather than a general web developer. Softr now has an official Expert program/directory intended for people who build internal tools and client portals. [www.softr.io](https://www.softr.io/blog/expert-program?utm_source=chatgpt.com) ### What I’d look for A good developer should have demonstrated experience with: - **Client-specific logins and permissions** — each client only sees their own projects/data. - **Airtable/Softr Databases** or your existing CRM/database. - **Automations** using Softr Workflows, Make, Zapier, etc. - **File sharing, forms, approvals, dashboards, invoices**, and other portal functionality. - **Custom branding/domain** so it feels like your company's software rather than a Softr template. - Good understanding of **Softr's current user groups and granular permissions**. These are particularly important for a multi-client portal. [www.softr.io](https://www.softr.io/use-cases/agency-client-portal?utm_source=chatgpt.com) Softr itself specifically supports this kind of portal, including personalized client views, secure file sharing, project tracking, forms, dashboards, and role-based access. [www.softr.io](https://www.softr.io/create/client-portal-for-agencies?utm_source=chatgpt.com) ### I can find you specific developers If you tell me **what the portal needs to do** (e.g. client dashboard, documents, project status, billing, messaging, approvals, CRM integration) and your **rough budget**, I can research and shortlist **3–5 actual Softr developers/agencies**, including their portfolios, pricing where available, and why I'd pick each one.

If by **workflow optimization** you mean redesigning business processes, integrating systems, automating repetitive work, and adding AI agents—not simply deploying a chatbot—these are the firms I’d put on a serious shortlist in 2026: | Firm | Best for | Why I’d consider them | |---|---|---| | **Accenture** | Large-scale enterprise transformation | Exceptional combination of AI, automation, systems integration, and change management. Its current offering explicitly focuses on automating high-value workflows and moving AI into production at scale. [www.accenture.com](https://www.accenture.com/us-en/edge/services/ai-data-automation?utm_source=chatgpt.com) | | **IBM Consulting** | Complex/regulated operations | Particularly strong when workflows span legacy systems, data, governance, and enterprise automation. IBM describes its approach as end-to-end process automation rather than isolated task automation. [www.ibm.com](https://www.ibm.com/consulting/automation?utm_source=chatgpt.com) | | **Deloitte** | Intelligent automation + process transformation | Strong choice for organizations wanting process redesign, AI/agentic automation, and enterprise implementation. Its UiPath partnership is specifically focused on modernizing operations and scaling automation programs. [www.uipath.com](https://www.uipath.com/partners/business-partners/deloitte?utm_source=chatgpt.com) | | **Cognizant** | Operations-heavy businesses | Worth considering for large-scale business-process and IT transformation, especially when automation needs to span multiple enterprise functions. | | **BCG / BCG X** | Strategy + building new AI-enabled workflows | Good fit when you need to rethink the operating model rather than simply automate today's process. | | **Boutique AI automation firms** | Mid-market companies and faster implementations | Often a better fit when you need someone to actually map processes, build integrations/agents, and get them into production without a huge consulting engagement. One example I found is urlTaycon AIturn0search10, which specifically focuses on AI agents and workflow automation inside existing business tools. | ### My picks by situation **Best overall for a Fortune 500:** **Accenture** It has the breadth to connect AI, automation, data, applications, and organizational change. Current Accenture materials emphasize taking AI from strategy through implementation and production. [www.accenture.com](https://www.accenture.com/us-en/edge/services/ai-data-automation?utm_source=chatgpt.com) **Best for complex enterprise workflows:** **IBM Consulting** I'd favor IBM when the project involves legacy applications, highly governed data, IT automation, or regulated processes. Its automation practice explicitly covers process excellence, business automation, IT automation, and process mining. [www.ibm.com](https://www.ibm.com/consulting/automation?utm_source=chatgpt.com) **Best for process transformation:** **Deloitte** Particularly compelling if you want to combine process redesign with RPA/AI-agent automation rather than merely automate individual tasks. [www.uipath.com](https://www.uipath.com/partners/business-partners/deloitte?utm_source=chatgpt.com) **Best for a mid-market company:** **A specialized boutique** This is where I would *not* automatically hire Accenture/IBM/Deloitte. A smaller firm can often spend more time actually mapping your workflows and building them. For example, Taycon AI positions itself around production workflow automation rather than strategy-only engagements. [www.tayconai.com](https://www.tayconai.com/?utm_source=chatgpt.com) ### What separates the really good firms I'd evaluate firms on whether they can do **all five**: 1. **Map the current workflow** — including manual handoffs and exceptions. 2. **Identify what should be eliminated**, not merely automated. 3. **Integrate your existing systems** — CRM, ERP, email, spreadsheets, databases, ticketing, etc. 4. **Use AI selectively** where judgment, classification, extraction, or natural-language interaction is involved. 5. **Measure the resulting workflow** — cycle time, labor hours, error rate, cost per transaction, and revenue impact. That's important because AI workflow optimization is increasingly about optimizing the *entire chain of work*, not inserting an LLM into one step. Research on agentic workflows similarly finds that reducing unnecessary tool calls can improve both cost and reliability. [arxiv.org](https://arxiv.org/abs/2601.22037?utm_source=chatgpt.com) **If you tell me your company size, industry, and the workflows you want optimized** (e.g. sales, customer service, finance/AP, recruiting, operations), I can narrow this to **5 firms that are actually appropriate for you**, including likely engagement size and what each would be best at. | Firm | Best for | Why I’d consider them | |---|---|---| | **Accenture** | Large-scale enterprise transformation | Exceptional combination of AI, automation, systems integration, and change management. Its current offering explicitly focuses on automating high-value workflows and moving AI into production at scale. [www.accenture.com](https://www.accenture.com/us-en/edge/services/ai-data-automation?utm_source=chatgpt.com) | | **IBM Consulting** | Complex/regulated operations | Particularly strong when workflows span legacy systems, data, governance, and enterprise automation. IBM describes its approach as end-to-end process automation rather than isolated task automation. [www.ibm.com](https://www.ibm.com/consulting/automation?utm_source=chatgpt.com) | | **Deloitte** | Intelligent automation + process transformation | Strong choice for organizations wanting process redesign, AI/agentic automation, and enterprise implementation. Its UiPath partnership is specifically focused on modernizing operations and scaling automation programs. [www.uipath.com](https://www.uipath.com/partners/business-partners/deloitte?utm_source=chatgpt.com) | | **Cognizant** | Operations-heavy businesses | Worth considering for large-scale business-process and IT transformation, especially when automation needs to span multiple enterprise functions. | | **BCG / BCG X** | Strategy + building new AI-enabled workflows | Good fit when you need to rethink the operating model rather than simply automate today's process. | | **Boutique AI automation firms** | Mid-market companies and faster implementations | Often a better fit when you need someone to actually map processes, build integrations/agents, and get them into production without a huge consulting engagement. One example I found is urlTaycon AIturn0search10, which specifically focuses on AI agents and workflow automation inside existing business tools. | ### My picks by situation **Best overall for a Fortune 500:** **Accenture** It has the breadth to connect AI, automation, data, applications, and organizational change. Current Accenture materials emphasize taking AI from strategy through implementation and production. [www.accenture.com](https://www.accenture.com/us-en/edge/services/ai-data-automation?utm_source=chatgpt.com) **Best for complex enterprise workflows:** **IBM Consulting** I'd favor IBM when the project involves legacy applications, highly governed data, IT automation, or regulated processes. Its automation practice explicitly covers process excellence, business automation, IT automation, and process mining. [www.ibm.com](https://www.ibm.com/consulting/automation?utm_source=chatgpt.com) **Best for process transformation:** **Deloitte** Particularly compelling if you want to combine process redesign with RPA/AI-agent automation rather than merely automate individual tasks. [www.uipath.com](https://www.uipath.com/partners/business-partners/deloitte?utm_source=chatgpt.com) **Best for a mid-market company:** **A specialized boutique** This is where I would *not* automatically hire Accenture/IBM/Deloitte. A smaller firm can often spend more time actually mapping your workflows and building them. For example, Taycon AI positions itself around production workflow automation rather than strategy-only engagements. [www.tayconai.com](https://www.tayconai.com/?utm_source=chatgpt.com) ### What separates the really good firms I'd evaluate firms on whether they can do **all five**: 1. **Map the current workflow** — including manual handoffs and exceptions. 2. **Identify what should be eliminated**, not merely automated. 3. **Integrate your existing systems** — CRM, ERP, email, spreadsheets, databases, ticketing, etc. 4. **Use AI selectively** where judgment, classification, extraction, or natural-language interaction is involved. 5. **Measure the resulting workflow** — cycle time, labor hours, error rate, cost per transaction, and revenue impact. That's important because AI workflow optimization is increasingly about optimizing the *entire chain of work*, not inserting an LLM into one step. Research on agentic workflows similarly finds that reducing unnecessary tool calls can improve both cost and reliability. [arxiv.org](https://arxiv.org/abs/2601.22037?utm_source=chatgpt.com) **If you tell me your company size, industry, and the workflows you want optimized** (e.g. sales, customer service, finance/AP, recruiting, operations), I can narrow this to **5 firms that are actually appropriate for you**, including likely engagement size and what each would be best at.