Weavable

About Weavable

Weavable is a SaaS context-infrastructure platform that provides AI agents with persistent, live work context by consolidating updates from the tools a business already uses. It presents a single MCP endpoint so agents query curated, up-to-date contexts instead of repeatedly ingesting raw records.

Review

Weavable focuses on reducing token usage and improving agent consistency by maintaining an activity graph and change log that represent ongoing work signals. It connects to common apps via scoped OAuth, reconciles relationships across sources, and returns ranked, denoised context slices for downstream models to reason over.

Key Features

• Continuous activity graph / changelog that maps updates and relationships across tools.
• One MCP endpoint to serve curated contexts to agents, reducing the need for multiple direct app connections.
• Pre-built connectors for common business apps (examples include HubSpot, Slack, Zendesk, Jira, GitHub, and email) with scoped OAuth access.
• Context definitions: create reusable, scoped views (customer health, pipeline slices, support context) that teams and agents can query.
• Governance and audit logging so queries, retrieved signals, and access rules are tracked for compliance and review.

Pricing and Value

Weavable follows a SaaS model and offers a 30-day free trial with full access and no credit card required to start. The platform's primary value proposition is cost and efficiency savings: by serving precise, pre-ranked signals rather than raw records, Weavable reports up to a tenfold reduction in token usage on realistic workflows such as pre-meeting briefs and renewal analysis. That reduction can lower LLM inference costs and cut latency from multiple round trips against disparate data sources. Expect subscription pricing after the trial; as an early-stage product, exact tier details and enterprise packaging may evolve.

Pros

• Significant token and latency savings for multi-source agent workflows by avoiding repeated ingestion and iterative retrieval loops.
• Scoped OAuth connectors and context-level access controls reduce permission sprawl and simplify agent permissions management.
• Reusable, curated contexts let multiple agents share the same authoritative view of relevant work data.
• Audit logging gives visibility into which agents and users accessed which signals, helping with compliance and troubleshooting.

Cons

• Newly launched product - integrations, enterprise features, and edge-case stability may still be maturing.
• Requires upfront design and curation of contexts and access rules; teams will need to invest time to model useful views and governance boundaries.
• Relies on downstream LLMs and inference infrastructure, so behavior can vary with model choice and may require testing across models.

Overall, Weavable is best suited for engineering, support, sales operations, and automation teams building multi-agent or agentic workflows on top of real business systems who need accurate, up-to-date context without token waste. Small-scale experiments or teams that only require static snapshot RAG may find the setup overhead less compelling, while teams handling frequent, cross-tool workflows will likely see the most benefit. Learn more or start a trial at weavable.ai.

Open 'Weavable' Website