SleekFlow

Named connectors plus a builder that creates the ones that do not exist, documented in unusual operational detail. Native integrations with Shopify, HubSpot and Salesforce give agents live customer data, and Stripe powers in-chat payments. Where no connector exists, the Custom API Integration builder takes the API however the customer has it (a described use case, uploaded documentation, documentation pasted into a setup chat, or a raw cURL command) and generates an editable schema.

SleekFlow's own page adds that AgentFlow will search public API endpoints or analyze an internal swagger and build the integration. Action is scoped: an integration must be enabled per agent under Configuration then Actions before a playbook can reference it, and the integration controls what the API can do and which fields are available while the playbook controls when to call it. Agents retrieve external data, trigger actions and update records mid-conversation, and playbooks chain several APIs from availability lookup through booking to payment.

Sourcehelp.sleekflow.io/en_us/sleekflow_ai/custom-api-integrations-in-sleekflow-airead 2026-09-05

Playbooks sequence multi-step work across several systems inside one conversation. SleekFlow says playbooks orchestrate how AI agents call multiple APIs in sequence, from availability lookups through booking confirmations to payments, so an entire transaction completes without leaving the chat, and the agent decides when to collect information, when to call the API and how to use the response according to playbook instructions.

Agents are trained on the customer's standard operating procedures so they handle complex scenarios like a good human agent, from sharing pricing estimates to resolving booking conflicts and executing returns. The vendor draws the line itself: a chatbot follows a fixed script and breaks off-script, while an agent understands context and takes action, updating contact profiles, moving leads down the pipeline, booking appointments and resolving requests without a human stepping in. Flow Builder handles the deterministic automations alongside.

Sourcesleekflow.io/agentflowread 2026-09-05

A maintained corpus the customer builds, edits and can see behind every answer. AgentFlow crawls a website and scans internal documents and turns them into structured knowledge articles, and the customer can see how the AI has organized that information and edit it directly, so the corpus is under their control rather than an opaque index. Grounding is visible at the point of use: every AI response shows the knowledge article it referenced.

Maintenance is a documented loop, with humans flagging knowledge gaps, correcting misunderstandings and sharing good human replies as examples, and knowledge updates passing through approval before they take effect. The inbound agent page adds that agents are trained on the customer's SOPs so they handle complex scenarios to the letter. This corpus is also what SleekFlow markets as AI memory.

Sourcesleekflow.io/agentflowread 2026-09-05

Guardrails and handoff are both settings the customer configures, documented step by step. The agent configuration guide says an administrator teaches the agent business knowledge, shapes how it speaks, sets guardrails for sensitive topics, and defines when it should hand off to humans, so the operator draws the boundary rather than accepting a default.

Changes are gated too: knowledge updates, playbook refinements and tone adjustments are reviewed and approved in one place rather than taking effect silently, and humans flag knowledge gaps, correct misunderstandings and promote good replies as examples. At run time agents work alongside people in the shared inbox with suggested responses, and high-priority cases route to a person.

Sourcehelp.sleekflow.io/agentflow/configuring-your-ai-agents-in-agentflowread 2026-09-05

Both certifications and controls are on the vendor's own pages. Certifications cover ISO 27001 certified security, a SOC 2 Type II audit verifying that all AI inputs and outputs are encrypted in transit and at rest, and stated full GDPR compliance. Customer data is logically isolated and never accessible to other AgentFlow users, SleekFlow says it never reviews a customer's AI data unless they explicitly opt in, and it commits that neither SleekFlow nor its AI providers use customer data to train or fine-tune models.

Role-based permissions govern who does what in the shared inbox, and the agent configuration surface lets an administrator set guardrails for sensitive topics. A no-training commitment that covers downstream providers is a control a buyer can hold the vendor to. No trust center or obtainable report is published, so the certifications rest on SleekFlow's own statement and the SOC 2 report is not public.

Sourcesleekflow.io/agentflowread 2026-09-05

Per-response tracing that names the reasoning, not just the outcome. SleekFlow states that every AI response shows its source: the knowledge article it referenced, the playbook step it followed, and how it interpreted customer intent, framed explicitly for audit. Showing the intent interpretation alongside the source and the step reveals why the agent went where it went, not only what it said. Above the individual response, AgentFlow analyzes every conversation to spot patterns, find gaps and plan improvements, and surfaces those as AI insights a team reviews.

Sourcesleekflow.io/agentflowread 2026-09-05

SleekFlow's AI memory is its knowledge base under another name. On the AgentFlow page the memory language sits inside the knowledge section: crawl your website, scan internal docs and turn them into structured knowledge articles, see how the AI organizes information and make edits, manage your AI memory not a black box, and human feedback expands AI memory so agents do not repeat the same mistake.

What is managed, edited and expanded is the article corpus, and improvement from real-world interactions is learning absorbed into a model rather than a memory layer. State does carry, because agents live inside the customer's CRM, collecting and enriching contact data and updating lifecycle stages, so an agent meeting a returning contact reads their record and history. That is retrieval against a CRM the customer owns, with no documented scope, lifetime or deletion control for state the agent itself retains.

Sourcesleekflow.io/agentflowread 2026-09-05

No hosting region, cloud provider, data center or residency option is stated on SleekFlow's product pages. What is documented is adjacent: customer data is logically isolated and never accessible to other AgentFlow users, SleekFlow states full GDPR compliance, and AI inputs and outputs are encrypted in transit and at rest as verified by SOC 2 Type II.

Logical isolation is a tenancy property and GDPR compliance is a legal posture; neither says where data sits or lets a customer choose. This matters more than usual for a vendor headquartered in Singapore and Hong Kong with customers across Europe, the Middle East and Brazil.

Sourcesleekflow.io/agentflowread 2026-09-05

A named starter set, but a set rather than a catalog. SleekFlow says AgentFlow comes with ready-to-use templates for common inbound scenarios, naming lead qualification, appointment booking and support resolution, and the help center carries a template aimed at support teams automating FAQ replies at volume.

From a template the customer customizes by uploading a knowledge base, indexing their website, adding custom answers or connecting CRM data, and most teams get a first agent live without writing code. Three named scenarios and a handful of playbook patterns make a starter set rather than a browsable library, and no agent gallery or marketplace is documented.

Sourcesleekflow.io/agentflow/inbound-ai-agentread 2026-09-05

Wide channel coverage with varied trigger types, and the channel mix is SleekFlow's clearest strength. Coverage spans WhatsApp as an official Meta partner, Instagram, Facebook, TikTok, Telegram, WeChat, SMS, email including Outlook, and voice calls, which is unusually broad in the messaging-first markets SleekFlow serves across Southeast Asia, the Middle East and Brazil.

Work starts several ways: inbound conversation on any channel; social triggers including TikTok instant forms, ad click-to-message and comment auto-replies that turn a public comment into a private conversation; behavior-based automations; and outbound proactive outreach and retention campaigns, which the vendor sells alongside inbound support. Custom API integrations let an agent act mid-conversation on a signal from an external system.

Sourcesleekflow.io/agentflowread 2026-09-05

No model selector, routing configuration or bring-your-own-key path is documented on any SleekFlow surface, and no provider is named first-party. The AgentFlow page confirms third parties are involved without identifying them, stating that SleekFlow and its AI providers never use customer data to train or fine-tune their models, so a model layer exists that the buyer neither chooses nor sees. Press coverage in 2025 named GPT-4o as the underlying model, but which model a vendor runs is not the same as the customer being able to choose, and nothing suggests they can.

Sourcesleekflow.io/agentflowread 2026-09-05

SleekFlow operates its own API, though its documentation is not public and access is gated by tier. A third-party connector guide tells users to obtain a SleekFlow API key, refers to SleekFlow API documentation for available endpoints, and says the key requires an Enterprise or Premium plan.

What is documented first-party runs the other way: a Custom API Integration builder where the customer describes an API use case, uploads documentation, pastes documentation into a setup chat or pastes a raw cURL command, and SleekFlow generates an editable schema the agent then calls, enabled per agent under Configuration then Actions. That is the platform reaching into the customer's systems.

Sourcehelp.sleekflow.io/en_us/sleekflow_ai/custom-api-integrations-in-sleekflow-airead 2026-09-05

A documented improvement loop with an approval gate, but no test before customers meet the change. AgentFlow analyzes every conversation to spot patterns, find gaps and plan improvements, surfaces those as AI insights, and routes knowledge updates, playbook refinements and tone adjustments through review and approval in one place, so a change is deliberate rather than automatic.

Humans flag knowledge gaps and correct misunderstandings, and performance is tracked. No simulation, staging environment, scenario suite, regression run or scored evaluation of a proposed agent before release is published, so the loop runs on live traffic and the approval gates the content of a change rather than testing its effect.

Sourcesleekflow.io/agentflowread 2026-09-05

No browser control, hosted session or interface automation is documented. Agents act through programmatic routes: native Shopify, HubSpot and Salesforce connections, custom API integrations built from a schema the customer supplies, and Stripe for in-chat payment, and they reach people over WhatsApp, Instagram, TikTok, SMS, email and voice. SleekFlow contrasts itself with scripted chatbots, not with interface-driving agents, and nothing in the platform operates a screen.

Sourcesleekflow.io/agentflowread 2026-09-05