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AI is changing how teams work, but it's hard to handle many tools while keeping costs low, safe, and easy to grow. This guide looks at five platforms - Prompts.ai, Domo, Lindy, VectorShift, and Gumloop - made to help AI work well for any team size. Here's what you should know:
Each platform shines in its way, whether it's saving money, showing data, making jobs easy, or keeping things safe. Pick the one that fits your team's needs and know-how.
| Spot | Main Aim | Top Points |
|---|---|---|
| Prompts.ai | All-in-one AI job steps | Use 35+ AI types, track costs live, top safety, help from experts |
| Domo | Mix data and get clear views | Over 1,000 ways to connect data, see data easy, easy to mix data ways |
| Lindy | Make tasks easy | Chat paths, work with many agents, make customer help better |
| VectorShift | Keep data safe and fit rules | Meets SOC 2, GDPR, HIPAA rules, strong code lock, PII clean-up |
| Gumloop | Easy workflow set up without code | Easy to use setup, over 100 parts, change flows as needed |
Key point: If you are watching your budget and using many AI tools, Prompts.ai has great deals and easy use. When you need data to make choices, Domo is top-notch. For tasks done by machines, Lindy and Gumloop are custom-fit, and VectorShift keeps things safe in touchy data spots.
Prompts.ai is a strong work tool made to make AI work easy by putting over 35 big word models in one safe, single way to see them. It handles the hard job of using many AI tools, helping groups cut down on money spent and keep high safety. Here's why Prompts.ai is special.
Prompts.ai is bendy, letting groups use any big word model without sticking to just one maker. From GPT-4 and Claude to LLaMA and Gemini, users can get to these models easy through one spot. This ends the hard job of using many accounts and ways to put things together. The setup also backs changeable paths, letting A/B checks of prompts without needing to code or mess up how work flows.
By keeping prompt control out of code, Prompts.ai lets users who don't code change talk templates with no need for a coder. Teams can start with what prompts are there, making it easy to make good AI talk ways for all sorts of work.
Prompts.ai shows very clear info on AI money use with built-in use checks that watch costs as they happen. The platform's TOKN Credits idea lets groups share and handle credits well, changing set AI costs to a pay-as-you-use plan. This way has cut AI money needs for groups by up to 98%.
| Plan Type | Monthly Cost | TOKN Points | Main Goodies |
|---|---|---|---|
| Pay When Needed | $0 | Few | 1 Area, 1 User, 1GB Space |
| Creator | $29 | 250,000 | For Self, 5GB Space |
| Main Business | $99/user | 250,000 | All Areas Open, 10GB Space |
| Pro Business | $119/user | 500,000 | More Tools, 10GB Space |
| Top Business | $129/user | 1,000,000 | Top Level, 10GB Space |
Every plan has compliance checks, rule tools, and shared storage built-in. These help even small teams keep high-level safety and run strong data rules on all AI interactions.
Prompts.ai offers more than just tools; it gives direct startup help and top-tier learning. Users can also join a lively group of prompt experts. The platform's Prompt Engineer Certificate program lets groups grow their own skills, making teams able to craft good prompts and tune their processes by themselves.
Domo is a tool for smart work that helps teams work better with AI by joining data and using AI well. Its key part is how it mixes many types of data and AI setups, making it easy for groups to work on AI tasks. Let's dig into how Domo's mix-and-match tech and custom tools boost AI jobs.
Domo is great at AI team work as it lets many AI types work at once. It uses AI from OpenAI, Anthropic, watsonx.ai, and Databricks, so teams can pick what they like without sticking to one option.
The Cloud Amplifier of the platform hooks up with over 1,000 data spots, like Snowflake, AWS, Google BigQuery, Azure, Oracle, and Salesforce. This wide link lets teams pull data from tools they already use and put it into AI work, cutting out hard data moves.
Domo also makes it easy to use learning models with a simple drag-and-drop setup. This lets anyone, even without tech skills, add models from places like watsonx.ai and Databricks into data paths easily, getting deep insights without needing to code. These mixing skills help make a solid base for custom work flows in Domo.
With MagicETL, teams can mix AI models right into data change steps. This lets data experts use AI tools from places like watsonx.ai and Databricks to train models and make new data in their paths. This smooth link boosts how automatic the system is and helps make data setup better.
Domo's ML tools also grow what it can do by letting in creative AI models from partner spots. These tools help teams make custom AI tools made just for what they need, from making apps to cleaning and setting up data. By using these parts, teams can make their work flows better and find new ways to use AI for smart ideas.
Lindy lifts AI work to a new level by bringing in talking agents meant to help how teams work. This AI tool lets groups set up smart flows using special talking AI agents. With Lindy, teams can deal with hard tasks in many systems and data spots, giving a new way to work with AI together.
Lindy's easy build fits well with many AI types and systems. Teams can pick from different words models based on the job. For one task, a model good at thinking and sort data might be used, and for another, a more art-like model for making stuff.
The tool joins with work tools like Slack, Google Workspace, Salesforce, and HubSpot. This lets teams build agents that get data from these, work with it through AI, and send the info back right. By linking these tools, Lindy makes flows smooth and helps share data well across spots.
Lindy also has a multi-agent system, where expert AI agents work together on parts of a flow. Like, one agent might get user data, another looks at it, and a third makes fit replies. This split way makes hard flows easy and makes sure steps get done right.
Lindy is great for making flows that fit what teams need. By using daily words, the tool lets users say what they want done, and it puts up the needed flows. This talking set up is easy to use, even if you don't know tech things well.
From easy data put-in to big choices, Lindy’s agents do many jobs. The platform uses if-this-then-that logic, letting agents make choices from the info they get. This change makes it easy to run flows that used to need people to check often.
To help more, Lindy has flow models for things like checking leads, helping customers, and making content. Teams can change these to what they need. Plus, the platform keeps an eye on how flows do, letting groups fix and make their agents better over time. It's all safe and firm.
Lindy puts safety first with top-line coding for data, both moving and sitting. It meets SOC 2 Type II rules and keeps detailed logs of what AI agents do, helping teams stay right with rules.
Leaders can set roles to say who can make, change, or use AI agents. This keeps work changeable but safe.
For groups with tight data needs, Lindy has places for data options so data can stay in certain spots. Plus, the tool works with own systems through safe API ties, giving a safe yet able way to handle touchy data while using AI help.
VectorShift is a safe AI tool set up for group work that holds key data. It's made just for fields where keeping data safe and staying with rules are top musts.
The tool works well with many AI types and sources while keeping tight rules on data. With set deals (DPAs) with groups like OpenAI, VectorShift makes sure that user data is not used for AI learning. These parts build a strong base for the tool’s top safety steps.
VectorShift sticks to SOC 2 Type II, HIPAA, and GDPR rules, using AES-256 to lock data not moving and TLS 1.3 for data moving. Roles saying who can enter data (RBAC) give more safety. The tool has steady safety checks, tests for weak spots, and has built-in PII filters and LLM guards to keep data safe. For very key data, more lock layers, tight entry rules, and non-stop checks are set. The tool also keeps data use low and has a firm no-sell rule.
To help safe AI work, VectorShift keeps giving out security lessons. These help the team know the best ways to handle key data in AI setups.
Gumloop is an easy-to-use AI tool that helps people who don't know code to set up their own AI tasks. It has a simple drag-and-drop system that makes it easy to start and handle these tasks.
Gumloop's main feature is its screen where groups can put together "Flows" from different "Nodes" like web scraping, PDF reading, or AI data grabbing. For bigger tasks, "Subflows" keep things neat and save time.
Omid G from Marketer Milk took note of how well Gumloop changes by making a blog post tool. This tool mixes a keyword Flow with a Subflow for Google looks and pulling out structured data.
Gumloop can do a lot more, with branching, looping, and if-then choices. You can make it start doing things from emails, Slack, webhooks, and more. From sending emails to handling docs, it can do lots of tasks. With over 100 built-in nodes and extras, there are many ways to tie it with other apps.
A marketing group tried out five workflows - checking leads, changing old posts, SEO checks, social media plans, and email sorting. They saw great results: a 65% rise in meetings and saved about 10 hours a week on usual work.
"Gumloop has been critical in helping all teams at Instacart - including those without technical skills - adopt AI and automate their workflows, which has greatly improved our operational efficiency."
– Fidji Simo, CEO @ Instacart
The platform has built-in AI tools like Categorizer, Ask AI, Summarizer, and Extractor. Teams can change prompts, pick from top models like GPT-4, Claude, Cohere, Gemini, and Deepseek, or use their own API keys for more control. Yet, for teams that need very special setups or high-end custom scripts, Gumloop might not fit all their needs.
Gumloop focus a lot on keeping things safe and in line with rules. It matches top security rules, such as SOC2 Type II and GDPR. It also fits with the EU-U.S. Data Privacy plan and the UK part, watched by the Federal Trade Commission. These steps make sure groups can deal well with secret data, mainly in areas with a lot of rules or when they handle a lot of customer info.
From the deep checks done above, here is a quick look at what these sites do well and what they don’t. This will help you match what each site can do with what you need for your work and tech needs.
Prompts.ai has a way in to over 35 AI types, can track costs in real time and cut AI costs by up to 98%, has top-level safety, easy start steps, and a busy group of prompt engineers.
Domo is great at mixing AI info into easy-to-understand data pics and reports, making it a top pick for choices based on data.
Lindy makes it easy to run work routines with normal talk, making easy tasks - specially in helping customers - work better.
VectorShift works on mixing vector data with meaning search, making it best for holding big-scale doc stores and know-how centers.
Gumloop lets users with no tech skills make AI work steps with simple drag-and-drop moves.
Look at the table below for a quick view of what each site mainly focuses on and their key cool things:
| Platform | Main Focus | Top Features |
|---|---|---|
| Prompts.ai | Easy model use and clear costs | Use 35+ AI models, track costs as they happen, top-notch security, help from community |
| Domo | Turning data into graphs and smart business help | Makes reports and data easy to see and use |
| Lindy | AI helps with work tasks | Set up work flows with easy talk, best for help with customers |
| VectorShift | Mixing big sets of words and smart search | Made for looking after big files of words and facts |
| Gumloop | Simple tool to make work flows | Easy move-and-set way for those new to tech |
When picking a platform, think about what your group knows well and what you need to do. If you want one way to get many AI models and clear cost plans, Promots.ai is good. Some other platforms might fit better if you need to focus on things like showing data or keeping documents.
Many use big platforms because they can trust the safety, like SOC2 checks and GDPR. Also, good learning and start-help is key to use it right. Look well at how each platform handles these parts to see if it fits what your group wants and aims for.
The best AI workflow tool depends on what your team needs and wants. Each one has its own strong points; they handle things like easy use, cost keeping, and safety in different ways.
Prompts.ai shines as a full package for managing AI workflows. It gives you over 35 AI models and real-time cost watching that can bring down AI costs by up to 98%, great for groups who watch their budgets and need top-level safety. It's got a large group of prompt engineers and an easy start-up process. This makes it a good pick for companies just beginning with AI or mixing many tools. Research teams gain from model comparisons and deep cost details, making their money go further.
Other platforms fit more set needs. Domo is made for teams making data into useful bits and clear boards for leaders. Lindy focuses on easing customer service with words tools, good for smaller shops. VectorShift is top for sorting big sets of papers with smart search, and Gumloop fits folks who aren't tech-savvy, letting them build AI workflows easily.
Prompts.ai lets teams cut down on AI costs with its pay-as-you-go TOKN system, which can drop costs by up to 98%. It gathers more than 35 leading language models in one spot, doing away with the need to handle many vendor subs, making work easier and cutting extra costs.
The site also has strong tools for cost control, like FinOps, which show how much is spent on AI as it happens. These tools help teams keep a close watch on their money and make smart choices, seeing to it that cash is used well and financial control over AI work is kept.
VectorShift takes data safety very seriously, sticking to rules like SOC 2, GDPR, and HIPAA. They make sure all data is hidden by encryption, keeping it safe from eyes that should not see it. They often check their security to find and fix any weak spots before they become a problem.
The company also makes sure to have strong deals in place with model providers, making sure that they never use client data for training. These steps help build a strong and reliable system to keep important data safe during all teamwork parts.
