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Loma
Pricing
- Model
- Free
Summary
Every Claude session your developer starts, every ChatGPT response your support rep sends — the learning dies when the tab closes. Loma is an open-source agent layer built to stop that loss, watching what your team does and compounding it into shared memory that agents can act on.
Loma sits across your tools — Slack, docs, CRM signals — running agents that handle pre-meeting briefs, RFP responses, bug triage, and onboarding health checks without waiting to be asked. The differentiating claim is the context layer: every resolved ticket, closed deal, and fixed bug is stored as a pattern or skill that future agents draw on, so day 100 is meaningfully faster than day 1. Self-hosted under Apache-2.0, it supports Claude, GPT, and Gemini with swap-anytime routing. The vendor states agents complete RFP questionnaires at ~95% coverage, flagging the remainder for human review. Where it strains is in the gaps the scraped content leaves open — enterprise auth, SLA guarantees, and mature operational tooling are not documented.
Bottom line: Pick Loma if your team runs Slack-centric workflows and you need shared AI memory across functions without a SaaS vendor holding your data — plan a harder conversation if your procurement team needs signed SLAs or SOC 2 before a tool touches customer data.
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Pros
Sign in to edit- Shared context layer that persists learned patterns across every agent run, which means the fifth RFP your agent completes draws on answers from the previous four rather than starting cold.
- Provider-agnostic LLM routing across Claude, GPT, and Gemini, so when API costs spike or a model underperforms on a task type, you swap the model without rebuilding the agent.
- Self-hosted under Apache-2.0, which means deal playbooks, customer health signals, and diagnostic patterns never leave infrastructure you control — critical for teams whose security review would otherwise block a SaaS AI layer.
- Slack-native task delegation — agents accept @mention assignments and post proactive briefs without requiring a separate interface — so adoption doesn't depend on getting your team to open another tool.
- Agents flag what they cannot answer rather than hallucinating completions — the RFP workflow surfaces unanswered questions for human review, so you review exceptions rather than auditing every output.
Cons
Sign in to edit- Compliance-gated procurement breaks here: the public documentation carries no mention of SOC 2, HIPAA readiness, or signed SLAs, so any team whose security review requires those artifacts before a tool touches customer data will stall at the vendor assessment stage — at which point they evaluate managed alternatives that ship compliance docs.
- The context layer's value depends entirely on volume and quality of team activity flowing through Loma — a team of three running occasional tasks builds sparse patterns, and sparse patterns mean agents are not meaningfully better than a cold prompt for months; smaller teams report this lag as the tool failing to deliver on its compounding premise.
- Enterprise access controls — role-based permissions, audit logs, SSO — are not described anywhere in the vendor's public documentation; teams operating in regulated industries or with strict data governance requirements are left to build these controls themselves or accept the risk, and several will choose a commercial platform instead.
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About
- Platforms
- Self-hosted, Slack, web dashboard
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-07-02T20:17:21.581Z
Best For
Who it's for
- Organizations wanting self-hosted agent orchestration
- Companies using mixed LLM subscriptions and open models
- Slack-centric workflows needing automated task execution
What it does well
- Pre-meeting briefs and post-meeting follow-ups in sales
- RFP and infosec questionnaire completion
- Bug triage and root-cause diagnosis
- Customer onboarding health monitoring and churn intervention
- Report and deck generation for QBRs
Integrations
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Frequently Asked Questions
- Is Loma free?
- Yes — Loma is fully free to use. There is no paid tier.
- Is Loma open source?
- Yes. Loma is open source.
- Can I self-host Loma?
- Yes. Loma supports self-hosting on your own infrastructure.
- What platforms does Loma support?
- Loma is available on: Self-hosted, Slack, web dashboard.
Hours Saved & ROI Stories Community
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Curated lists that include this category
Most teams treat AI as a series of one-off conversations — a question answered, a draft written, a bug explained, all of it evaporating when the session ends. Loma is an open-source agent platform that intercepts that waste. It deploys agents across sales, support, product, and engineering functions, each one feeding a shared context layer — patterns, skills, tone signatures — so the next agent picking up a similar task starts with institutional memory rather than a blank prompt.
The context layer is Loma’s sharpest edge. When a developer fixes a webhook retry bug, Loma stores the diagnostic pattern. When support resolves a KMS timeout, that resolution becomes a reusable skill. The vendor describes this as 847 stored patterns, 23 skills, and 156 customers tracked in a live demo — numbers that illustrate the compounding mechanic even if they are illustrative. For RFP and infosec questionnaires specifically, the docs describe agents pulling from existing SOC 2 reports, past submissions, and ISO docs to answer the bulk of questions automatically, flagging only the ones requiring legal or executive sign-off.
Loma fits organizations that already run fragmented LLM subscriptions — some teams on Claude, others on GPT or Gemini — and want a single layer that routes tasks without locking into one provider. The Apache-2.0 license and self-hosted deployment mean your data and learned patterns stay on infrastructure you control, which matters when the context layer holds deal playbooks and customer health signals. The ceiling appears when you need enterprise-grade access controls, audit trails for compliance, or guaranteed uptime — the public documentation does not address these, and teams with procurement gates around SOC 2 or HIPAA will find precious little to hand to their security reviewers.
Slack is the primary control surface: agents proactively post briefs before meetings, accept task assignments via @mention, and surface flagged items for review inside channels your team already monitors. The vendor lists Docker and Kubernetes as supported deployment targets, and the model layer is described as swappable at any time — switching from a paid API model to a local open model is a configuration change, not a migration.