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Getting Started
What is Swa? ▼
Swa is a multi-agent, multi-modal platform that integrates generative AI into Slack, Microsoft Teams, SMS, and WhatsApp. Access 10+ AI models from one interface with no per-user fees, no heavy data storage, and enterprise-grade security.
How do I install Swa? ▼
Visit our get started guide for one-click Slack installation. For Microsoft Teams and SMS, sign up at admin.swa-ai.com and follow the setup guide.
Is Swa compatible with free Slack/Microsoft Teams plans? ▼
Yes. Swa works with free Slack and Microsoft Teams plans. Some extended context features may be limited by the free-tier policies of those interfaces.
Using Swa
How do I use Swa? ▼
In Slack or Microsoft Teams, type @swa followed by your question in any channel. For SMS and WhatsApp, just text your question directly. Swa's intelligent routing automatically selects the best AI model for your query.
What AI models are available? ▼
Swa provides access to ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek, Llama, and more. You can also specify which model to use (e.g., "@swa ask claude to review this code").
Can I create custom agents? ▼
Yes. Just describe what you want in natural language. For example: "Create an SEO Writer agent using OpenAI that optimizes content for search engines." Your agent will be available via @swa.
Does Swa work in private channels? ▼
Yes. Invite Swa to any private channel and it will respond to @swa mentions. Content in private channels stays contained within that channel.
How does intelligent routing work? ▼
Swa automatically selects the best AI model for each query based on the task type, optimizing for speed, accuracy, and cost. You can also override the selection and specify a model directly, for example: "@swa ask claude to review this code."
What integrations does Swa support? ▼
Swa integrates with GitHub, Jira, Salesforce, ServiceNow, HubSpot, Outlook, Gmail, QuickBooks, PagerDuty, Datadog, and more. New integrations are added regularly. Visit the integrations page for the full list.
Pricing & Billing
How does billing work? ▼
Billing is monthly. You can upgrade, downgrade, or cancel your plan at any time with no long-term contracts or cancellation fees. Enterprise customers have the option of invoice-based billing with net-30 terms. All plans include a full usage dashboard so you can monitor spending in real time.
What if I exceed my token allocation? ▼
You will be notified well before you reach your limit so there are no surprises. If you approach your allocation, you can choose to upgrade your plan for additional tokens. We will never cut off your access without warning. You stay in control of your usage at all times through the admin portal.
How does pricing compare to other tools? ▼
Most AI tools charge $20 to $40 per user per month for team plans. Swa charges a single flat fee with no per-user pricing. For teams of 10 or more, that means savings of up to 90% compared to subscribing each team member to individual AI tools. And you get access to 10+ models instead of just one.
Do you offer nonprofit or education discounts? ▼
Yes, we offer special pricing for nonprofits, educational institutions, and open-source projects. Contact our sales team at support@swa-ai.com to learn more about eligible discounts and how to apply.
What is included in the free trial? ▼
The free trial includes 1,000,000 tokens, access to all AI models, file upload support, custom agent creation, and access across all interfaces (Slack, Microsoft Teams, WhatsApp, SMS). It is designed for individuals who want to test Swa before committing to a paid plan. No credit card required to start.
Security & Compliance
What security certifications does Swa have? ▼
Swa is SOC 2 aligned with a zero-retention policy for full data sovereignty. We support GDPR and HIPAA compliance, provide full audit trails, and process payments securely through Stripe (PCI Level 1 certified). Visit our security page for details.
Does Swa store my data? ▼
No. Swa operates on a zero-retention policy. Your messages and data are processed in real time and are not stored, logged, or used for model training. You maintain full data sovereignty at all times.
Is Swa GDPR compliant? ▼
Yes. Swa supports GDPR compliance with data sovereignty options, zero-retention processing, and full audit trails. For more details, visit our policies page.
Troubleshooting
Swa is not responding? ▼
Try these steps: (1) Check that Swa has been invited to the channel. (2) Make sure you're using the @Swa mention. (3) Restart the Slack/Microsoft Teams app. (4) If the issue persists, email support@swa-ai.com.
Installation errors? ▼
Verify that your workspace admin has approved the app installation. Check app limits on your Slack/Microsoft Teams plan. Try reinstalling from the install page. Contact support if the problem continues.
AI Basics
What is AI? ▼
AI is technology that performs tasks requiring human intelligence like understanding language, recognizing patterns, and making decisions by learning from data instead of following fixed rules.
How does AI work? ▼
AI analyzes large amounts of data to identify patterns and make predictions. It learns from examples, similar to how people learn from experience and repetition.
What is the difference between AI and machine learning? ▼
AI is the broad concept of intelligent machines. Machine learning is how modern AI learns, by training on data to improve without explicit programming.
What is generative AI? ▼
Generative AI creates new content like text, images, or code rather than just analyzing existing information. ChatGPT and Claude are examples that produce original responses.
What are AI models? ▼
AI models are trained systems that power AI applications. Different models excel at different tasks based on their training data and optimization goals.
Why are there different AI models? ▼
Different AI models excel at different tasks because they train on different data and optimize for specific purposes. No single model handles everything best.
What is a large language model? ▼
A large language model is AI trained on massive text datasets to understand and generate human language. LLMs power tools like ChatGPT and Claude.
What is the difference between narrow AI and general AI? ▼
Narrow AI performs specific tasks well like playing chess or recognizing faces. General AI would match human intelligence across all domains but does not exist yet.
Models & Agents
What is a multi-model AI? ▼
Multi-model AI uses multiple AI models together rather than relying on a single model. Different models handle different tasks, combining their strengths for better results.
Why use multiple AI models instead of one? ▼
Different AI models excel at different tasks. Using multiple models lets you choose the best tool for each job, improving accuracy and reducing errors.
What is an AI aggregator or AI orchestration platform? ▼
An AI aggregator/orchestration platform like Swa connects multiple AI models in one workspace. Users access ChatGPT, Claude, Gemini, and other models without switching apps and repeating prompts.
How do AI aggregators work? ▼
AI aggregators route your requests to selected models and return results instantly. You can compare outputs from different models to find the best answer.
What are the benefits of using multiple AI models? ▼
Multiple models reduce errors through cross-validation, combine complementary strengths, handle diverse tasks better, and provide backup options when one model fails or gets stuck.
Should I compare outputs from different AI models? ▼
Yes. Comparing outputs reveals where models agree, showing reliable information, and where they disagree, highlighting areas requiring your judgment before deciding.
Why do different AI models give different answers? ▼
AI models train on different data and optimize for different goals. This creates unique strengths and weaknesses, causing varied responses to identical questions.
How do I know which AI model to use? ▼
Match tasks to model strengths. Use ChatGPT for creative writing, Claude for reasoning and analysis, Perplexity for research with citations, and Gemini for multimodal tasks. With Swa, you have access to all models in one place.
What is model switching? ▼
Model switching means trying different AI models when one gets stuck or produces unsatisfactory results. Often another model solves the same problem successfully.
What is an AI agent? ▼
An AI agent is software that performs tasks automatically without constant human input. Unlike chatbots, agents take action like updating databases or monitoring systems.
How are AI agents different from chatbots? ▼
Chatbots answer questions. AI agents execute tasks. A chatbot tells you about the weather while an agent checks it and reminds you to bring an umbrella.
How do AI agents work under the hood? ▼
Many agents combine large language models with tool connectors, retrieval systems, state managers, and decision logic. They observe, plan, act, and update iteratively.
What is the difference between autonomous and assisted agents? ▼
Autonomous agents operate with minimal human intervention, making decisions within defined boundaries. Assisted agents support humans by suggesting actions requiring approval before execution.
What safety and governance measures are important for agents? ▼
Implement input/output validation, role-based access, rate limits, human review gates, logging for auditability, and content filters. Define clear boundaries and fail-safe behaviors.
What is AI orchestration? ▼
AI orchestration coordinates AI components like models, data flows, tool calls, and human steps into reliable workflows. It turns isolated models into production-ready systems.
What business benefits does AI orchestration deliver? ▼
It speeds deployments, reduces manual handoffs, improves reliability, and enables repeatable scaling. You get faster time-to-value, lower operational risk, and clearer audit trails.
What are the core components of an AI orchestration platform? ▼
Typical components include workflow runners, model and tool connectors, data managers, logging and observability, security controls, and interfaces for human-in-the-loop review.
How is AI orchestration different from MLOps? ▼
MLOps focuses on model lifecycle tasks like training and versioning. AI orchestration builds on that to coordinate models, external tools, prompt logic, and human steps.
What is intelligent routing in AI? ▼
Intelligent routing automatically sends each task to the AI model best suited to handle it. Simple tasks go to fast models, complex ones to powerful models.
How does AI task routing save time? ▼
Task routing eliminates manual model selection. The system automatically picks the right AI for each request, so you get better answers faster without switching tools.
What is AI workflow orchestration? ▼
AI orchestration chains multiple AI models to complete complex tasks. One model researches, another analyzes, another writes, all from a single command without manual coordination.
How do AI models work together? ▼
Models can work sequentially where each builds on the previous output, in parallel for comparison, or through routing where tasks go to specialized models automatically.
Can AI models cross-check each other? ▼
Yes. When multiple AI models analyze the same question, they often catch errors or biases in each other's responses, improving overall accuracy and reliability.
How does AI handle multi-step workflows? ▼
AI can execute multi-step workflows by chaining tasks together. One command triggers research, analysis, and writing sequentially, with each step building on previous results.
What is human-in-the-loop in orchestration? ▼
Human-in-the-loop injects human review, approvals, or corrections at defined workflow points to improve quality, safety, and training data for high-stakes decisions.
AI in Practice
How do I integrate AI into my existing tools? ▼
AI platforms can integrate with tools like Slack, Microsoft Teams, email, and databases through APIs, plugins, or native integrations, making AI accessible where you already work.
Can AI work inside Slack or Microsoft Teams? ▼
Yes. Many AI platforms integrate directly into Slack and Microsoft Teams, letting you access AI models through chat commands without opening separate apps or switching contexts.
What is context retention in AI? ▼
Context retention means AI remembers previous conversation history. You can ask follow-up questions or switch models without repeating information or losing conversation flow.
Can teams collaborate using AI? ▼
Yes. Team members can share AI conversations, build on each other's work, and maintain conversation context across multiple people contributing to the same project.
How does AI actually improve productivity? ▼
AI automates repetitive tasks like summaries and data extraction, augments decision-making with insights, and accelerates content generation. That frees people for higher-value work.
How should I measure AI-driven productivity gains? ▼
Use quantitative metrics like time saved, error rates, throughput, and cost per task plus qualitative metrics like user satisfaction and adoption rates tied to business outcomes.
How does AI detect fraud? ▼
AI analyzes transaction patterns to identify unusual activity indicating fraud. It flags suspicious behavior in real time by learning normal patterns and spotting deviations instantly.
How does AI personalize recommendations? ▼
AI analyzes your behavior, preferences, and patterns to predict what content, products, or services you might like. It learns from past choices to suggest relevant options.
What is Retrieval-Augmented Generation and when should I use it? ▼
RAG combines vector-searchable knowledge with language models so responses are grounded in your data. Use it for accurate answers over large document sets and knowledge bases.
When should I fine-tune a model versus rely on prompting? ▼
Start with prompt engineering for speed and lower cost. Fine-tune when you need consistent domain-specific behavior or performance not achievable via prompts alone.
How do AI models learn? ▼
AI models analyze patterns in training data. They adjust internal parameters millions of times until they accurately predict outputs for new inputs they have never seen.
What is reinforcement learning? ▼
Reinforcement learning trains AI by rewarding good actions and penalizing bad ones. The AI learns optimal strategies through trial and error, similar to learning from consequences.
What is supervised learning? ▼
Supervised learning trains AI using labeled examples. The AI learns by seeing correct answers repeatedly, then applies patterns to make predictions on new, unlabeled data.
What is unsupervised learning? ▼
Unsupervised learning trains AI on unlabeled data to find hidden patterns. The AI groups similar items or identifies anomalies without being told what to look for.
What is transfer learning? ▼
Transfer learning applies knowledge from one task to another related task. An AI trained on general language can be fine-tuned for specific tasks efficiently.
Why are per-user AI fees expensive? ▼
Per-user fees multiply quickly. With 50 people using three AI tools at $20-30 each, monthly costs reach thousands, even if most users need occasional access. Swa uses token-based pricing instead, allowing you to give anyone in the company access to AI.
How can I reduce AI subscription costs? ▼
Consolidate multiple AI subscriptions into platforms offering access to several models. Token-based pricing instead of per-user fees reduces costs while increasing team access.
What is AI vendor lock-in? ▼
Vendor lock-in occurs when you build workflows around one AI provider. If they change pricing, deprecate features, or shut down, your workflows break completely.
How do I avoid AI vendor lock-in? ▼
Use platforms that support multiple AI providers. Build workflows that can switch between models easily, ensuring you are never dependent on a single vendor's decisions.
How do we get started choosing an orchestration approach or vendor? ▼
Define your use cases, data needs, compliance constraints, and integration points. Pilot small, measure impact, and prefer platforms with flexible connectors and strong observability.
AI Safety
Can AI make mistakes? ▼
Yes. AI can generate incorrect information confidently. Always verify AI outputs for critical decisions and treat AI as a drafting tool, not truth.
What are AI hallucinations? ▼
Hallucinations occur when AI generates false information presented as fact. The AI predicts plausible responses based on patterns, not actual knowledge or understanding.
Is my data safe when using AI? ▼
It depends on the tool and configuration. Some AI services store conversations for training. Enterprise platforms often offer zero retention where data processes without storage.
What is zero retention architecture? ▼
Zero retention means your data processes in real time to generate responses, then gets immediately deleted. Your information never trains models or becomes accessible to others.
What is AI bias? ▼
AI bias occurs when models produce unfair or discriminatory outputs based on biased training data. If training data contains historical biases, AI learns those same biases.
What monitoring and observability does AI orchestration require? ▼
Monitor model outputs for accuracy, drift, latency, error rates, and cost. Capture detailed logs, input/output traces, and business KPIs for debugging and compliance.
What is ethical AI? ▼
Ethical AI refers to developing and using AI systems responsibly, ensuring fairness, transparency, privacy, accountability, and avoidance of harm to individuals or groups.
What is the future of AI? ▼
AI will become more autonomous with advanced reasoning, better integration across tools, and improved accuracy. Expect AI agents handling complex workflows while humans focus on strategy.
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