Aisera vs Thread (2026)

Aisera connects to more than a hundred enterprise applications, with native one-click integrations to systems including ServiceNow, Salesforce and Jira, and ships a library of over a thousand prebuilt actions covering create, read, update and delete operations, so agents write to systems of record as well as reading them. The platform automatically discovers and configures available tools, and agents query multiple platforms to validate data within a single diagnostic flow. Ingestion APIs and webhooks are available for teams that would rather not use the admin interface.

Sourcedocs.aisera.com/aisera-platform/llm-operations/understanding-llm-capabilities/aiseras-agentic-ai-for-itsmread 2026-09-05

Native connections reach the systems an MSP runs on, with write actions into the ticket record. Thread integrates with the three main MSP PSAs, ConnectWise PSA, Autotask and HaloPSA, plus Microsoft Teams, Slack and Microsoft 365, and the agents write into them as well as reading.

Triage sets ticket properties, categorizes, prioritizes, assigns a technician and creates time entries automatically, and Thread reports 96% accuracy on those properties.

Beyond the PSA, Thread connects to Rewst, Power Automate and Zapier for automation and to Pia for full ticket resolution, with Triage passing structured data into Pia to complete PSA and Microsoft 365 actions end to end.

Sourcegetthread.comread 2026-09-05

Aisera Unify orchestrates Universal, Domain Specific and Task agents that plan, reason and act across entire processes.

Its decisions rest on Multi-Criteria Decision Analysis, which weighs paths on success probability, execution time and resource requirements, Ensemble Decision Methods that combine reasoning approaches for consensus, Confidence Scoring with Decision Trees using confidence intervals and branching logic, and Historical Pattern Matching over past interaction data.

Hyperflows carry packaged multi-step automations, and the platform automatically discovers and configures available tools at runtime.

Sourcedocs.aisera.com/aisera-platform/llm-operations/understanding-llm-capabilities/aiseras-agentic-ai-for-itsmread 2026-09-05

Several specialized agents cover one journey end to end, with structured handoff between them and out to another platform. The System of Agents divides the service desk by job.

Triage identifies the request, gathers context and triggers the workflow, Overflow catches calls that would go to voicemail and escalates a P1 to the on call team, Reminder checks whether an issue is still live and closes threads that resolved themselves, and Memory maintains the contact record underneath.

Triage passes structured data into Pia to complete PSA and Microsoft 365 automation, so a routine password or access request finishes without a technician acting as middleman, and everything else routes to the right person with the ticket already categorized, prioritized and prepped.

Sourcegetthread.com/blog/magic-agents-a-new-era-of-ai-powered-automation-for-mspsread 2026-09-05

Work arrives through Microsoft Teams, email, web portals and chat. Proactive triggers let agents autonomously detect and remediate major incidents before they cause downtime, without a user request. In ITSM flows, agents also escalate automatically when response time or error rate crosses a critical threshold.

Sourcedocs.aisera.com/aisera-platform/llm-operations/understanding-llm-capabilities/aiseras-agentic-ai-for-itsmread 2026-09-05

Five channels include the two an MSP desk lives in, and work starts three ways. Agents chat, email and call across chat, email, phone, Microsoft Teams and Slack, and Teams and Slack matter because that is where an MSP's end users raise issues, not a help portal. Thread Voice AI is generally available and automates the phone channel with capture, transcription and automatic ticketing.

Work starts inbound, when a client messages or calls, on events, when the Overflow Agent picks up a call that would otherwise reach voicemail and escalates a P1 to the on call team outside hours, and proactively, when the Reminder Agent reaches back out to check whether an open issue is still live and closes the thread if it resolved itself. Traditional phone and email stay fully active alongside.

Sourcegetthread.comread 2026-09-05

Data sources are configured and ingested on a schedule or on demand. PDF, HTML, Markdown, PowerPoint, text and Box notes are converted through the Docling document converter, with optional OCR and accurate table parsing, and smart caching skips documents whose content has not changed. An Indexer job must finish before AI Learning or Content Generation can serve from the content. Documents can be retired so they stop serving user requests while staying in the source, and custom fields are mapped from the source schema into the platform. Aisera also maintains a knowledge graph and ontologies.

Sourcedocs.aisera.com/aisera-platform/adding-data-to-your-tenant/data-ingestionread 2026-09-05

Thread grounds its agents in ticket resolution history, knowledge articles and ITIL best practice, and builds a living service catalog from historical tickets, so categories and answers reflect how that MSP actually works instead of a generic taxonomy, and the catalog updates as tickets accumulate. Thread describes the underlying conversational dataset as the largest in the MSP market, drawn from more than 170 million tickets across 750-plus partners. Device, preference and issue history for each contact sits with the Memory Agent.

Sourcegetthread.comread 2026-09-05

No agent memory is described, and none is ruled out. In ITSM flows, agents keep conversation context across multiple diagnostic rounds within a session. Historical Pattern Matching uses past interaction data to inform decisions, which is learning built into an optimization model, and the Test Suite replays audited historical conversations from a stored transcript corpus. None of these is a memory that a customer can name, scope or delete. Tenant settings include Context Management and Conversations.

SourceAisera ITSM agentic documentation, Test Suite documentation and documentation index, docs.aisera.comread 2026-09-05

The Memory Agent, part of Service Intelligence, creates a living memory for every contact, remembering their devices, preferences and past issues and updating automatically as new interactions happen, so any technician on the desk can serve a client as if they already know them.

The platform forms this state from interactions and keeps it across separate conversations, tied to an identifiable contact, beyond a lookup against the PSA. MSP technicians rotate, and the memory is what carries over when they do. Ticket resolution history, ITIL practice and the service catalog built from historical tickets sit on the knowledge side.

Sourcegetthread.com/blog/magic-agents-a-new-era-of-ai-powered-automation-for-mspsread 2026-09-05

Guardrails under the TRAPS framework are enforced at runtime. A Content Moderation Service validates and sanitizes input at the ingress gateway and inside the service, system prompts are fixed at build time instead of taking free-form input, and out-of-distribution detection keeps agents to registered topics and domains.

A human curation step has named roles review any data before it enters model training, and PII anonymization and injection defense are also in place. Aisera's blog describes human confirmation loops that halt high-stakes actions until someone approves them, though the product documentation does not cover them.

Sourcedocs.aisera.com/aisera-platform/tenant-setup/security-and-privacy-trapsread 2026-09-05

The partner sets the autonomy boundary, and the end user always has a way out. Magic Agents are customized to the security and permissions each MSP needs, so the partner defines what agents may do in their clients' environments instead of accepting a default. Autonomy is bounded on purpose, with agents resolving 15 to 25 percent of tickets end to end and handing the rest to a technician fully prepped.

Thread says the AI's job is triage and information gathering and that anything complex hands off immediately with full context, and end users are told that typing "speak to an engineer" at any point bypasses the assistant entirely. Automations built on Rewst, Power Automate and Zapier are described as human in the loop. There is no approval queue before individual agent actions go out.

Sourcedocs.getthread.com/article/i6mm06bsv7-thread-partner-change-management-guideread 2026-09-05

Aisera holds SOC 2 Type II, audited yearly against the AICPA Trust Service Criteria for Security, Availability and Confidentiality with a risk management strategy submitted, along with ISO/IEC 27001 certification, Cloud Security Alliance STAR Level 1 certification for the SaaS, GDPR controls and CCPA compliance, and it signs HIPAA BAAs on request. A trust center sits at trust.aisera.com. Access controls include role-based access control with built-in user roles and permissions, platform permission definitions, user account and role management, and authentication settings.

Sourceaisera.com/platform/security-and-complianceread 2026-09-05

The security program is in place, but the SOC 2 attestation has not been issued yet. The Trust Center publishes continuous control monitoring across 107 controls, a subprocessor list, public data handling documents and restricted reports available on request.

Thread acts as a data processor with processing terms available on request, data is encrypted, communications are logged into the ticketing system, and Thread states customer data is not used to train Claude or any other model, not by AWS, not by Anthropic and not by Thread. The SOC 2 Type II audit is in progress, with a bridge letter available under NDA, and Thread tells partners not to describe it as SOC 2 certified until the report is issued. AWS and Azure hold SOC 2 Type II and ISO 27001 for the clouds Thread runs on, not for Thread itself.

Sourcedocs.getthread.com/security-billing/soc-2-and-compliance-statusread 2026-09-05

An Audit Trail logs every AI agent decision with timestamps and reasoning, AI Lens gives complete stack trace visibility into agent conversations and decision-making, and AI Workbench analyzes agent performance and unresolved conversations. The LLM gateway also has OpenTelemetry integration for full observability, and the customer receives that telemetry directly.

Sourcedocs.aisera.com/aisera-platform/llm-operations/understanding-llm-capabilities/aiseras-agentic-ai-for-itsmread 2026-09-05

Performance is measured, but execution is not traced. Thread reports ticket properties set at 96% accuracy, sentiment at 97% positive, resolution rates, hours returned to technicians and an ROI calculator, giving a desk manager a clear read on what the agents achieved across more than 170 million tickets.

Communications are logged into the ticketing system, so a conversation can be retrieved as a ticket record. There is no reasoning trace for each decision, tool call log, source attribution on an answer or configuration audit trail for an agent, so a manager can see that triage was 96% accurate without being able to reconstruct why a particular ticket was categorized as it was.

Sourcegetthread.comread 2026-09-05

Deployment and residency options are not published. There is no region menu, VPC, single tenant or on premises option, and the security and compliance material does not address residency. Data handling questions go to the trust center at trust.aisera.com.

Sourceaisera.comread 2026-09-05

Thread names one region and offers no choice. Data is held in the United States, application data lives in AWS US East in Northern Virginia, and Claude inference runs on Bedrock's US region capacity, with Azure carrying the other AI features. There is no alternative region, no location the customer selects, and no self hosted, private cloud or single tenant option. Thread acts as a data processor, with processing terms available on request and a subprocessor list published at the Trust Center.

Sourcedocs.getthread.com/article/2gttcwtp4a-thread-ai-on-aws-bedrock-anthropic-claude-data-processing-security-triage-agent-super-magicread 2026-09-05

Customers adopt a library of prebuilt Domain Specific Agents for IT, human resources and customer service, Hyperflows as packaged multi-step automations validated through a Test and Debug feature, and over a thousand prebuilt actions that teams can search, clone and modify. No-code, low-code and pro-code authoring covers the cases the library does not.

Sourcedocs.aisera.com/aisera-platform/llm-operations/understanding-llm-capabilities/aiseras-agentic-ai-for-itsmread 2026-09-05

A named agent set ships for an MSP to switch on, not a catalog to browse. The System of Agents has a Triage Agent that collects context, categorizes and routes, a Reminder Agent that checks whether issues are still active and closes resolved threads, an Overflow Agent that stops calls reaching voicemail, and a Memory Agent inside Service Intelligence.

Each works out of the box without a partner building it. The four agents are a product set, not a library a customer browses, and there is no template gallery. A community driven marketplace of service workflows and first party automations is on Thread's roadmap and not available today.

Sourcegetthread.com/blog/magic-agents-a-new-era-of-ai-powered-automation-for-mspsread 2026-09-05

Each query is routed to the best-fit large language model, and Aisera supports its own AiseraLLMs, third-party models or a model the enterprise brings itself. Routing happens inside a named LLM gateway that also carries the OpenTelemetry instrumentation. Customers can choose the model, including bringing their own, while Aisera also routes across models.

Sourceaisera.com/platformread 2026-09-05

Two model platforms are in use and Thread chooses between them. Claude runs inside AWS Bedrock for the Triage Agent and Super Magic features, Thread's other AI features run on Microsoft Azure, and these features are being turned on progressively. The platform runs across at least two providers, Anthropic through Bedrock and Azure OpenAI, and has moved a flagship agent from one to the other, but the selection sits with Thread. There is no model selector, routing policy or bring your own key path for customers, and a customer cannot choose which model handles their tickets.

Sourcedocs.getthread.com/article/2gttcwtp4a-thread-ai-on-aws-bedrock-anthropic-claude-data-processing-security-triage-agent-super-magicread 2026-09-05

Ingestion APIs and webhooks let teams configure data sources programmatically instead of through the admin interface, and tenant configuration includes a Tools section and a Federation Service. Aisera's platform marketing also claims native Model Context Protocol, agent-to-agent messaging and AGNTCY support, which the product documentation does not cover.

Sourcedocs.aisera.com/aisera-platform/adding-data-to-your-tenant/data-ingestionread 2026-09-05

There is no public API, SDK, webhook reference or MCP endpoint. Partners extend Thread through other platforms, with automation through Rewst, Power Automate and Zapier and full ticket resolution through Pia, so they connect a third party automation tool instead of calling Thread directly. A community driven marketplace of service workflows is on Thread's roadmap and not available today.

Sourcegetthread.com/blog/magic-agents-a-new-era-of-ai-powered-automation-for-mspsread 2026-09-05

The Test Suite replays entire audited conversations and phrases generated from ingested knowledge base articles, not just single utterances, and compares current bot responses against historical ones in a single click.

Each case returns Matched, meaning the response is consistent with historical data, or Unmatched, meaning it has deviated and a potential regression is flagged, with a Matching Score attached and an Execution Chat Simulation interface for inspecting unmatched cases.

A Test and Debug feature validates Hyperflows against simulated scenarios before production deployment, and Aisera says it continuously evaluates and optimizes agent performance through the test suite.

Sourcedocs.aisera.com/aisera-platform/ai-workbench-optimize-conversations/test-suiteread 2026-09-05

Outcomes are measured and backed by a commercial guarantee, but nothing tests a change before it reaches clients. Thread tracks triage accuracy at 96%, sentiment at 97% positive, resolution rates and hours returned, and backs it with a 60 day positive ROI guarantee or a refund. There is no simulation, staging environment, scenario suite, regression run or scored evaluation of an agent before release, so tuning happens against live client tickets instead of in a sandbox.

Sourcegetthread.comread 2026-09-05

Agents reach other systems through Aisera's integrations, ingestion APIs and webhooks, and its models run in secure environments behind access controls. No agent drives a browser, desktop session or remote computer.

Sourcedocs.aisera.com/aisera-platform/tenant-setup/security-and-privacy-trapsread 2026-09-05

There is no browser control, hosted session or interface automation. Agents work through integrations, writing into ConnectWise, Autotask and HaloPSA through native connections, handing structured data to Pia to complete PSA and Microsoft 365 actions, and reaching people over chat, email, Teams, Slack and phone. Where an action falls outside those connectors, the path is a third party automation platform such as Rewst, Power Automate or Zapier, not an agent operating a screen.

Sourcegetthread.comread 2026-09-05