The Agent Operations Platform
Get better results from every AI agent
AI is only as useful as the context it has. Improve and align your team's agents with better context.
Connect every agent your team uses
Problems by role
Your agent problem depends on where you sit.
Choose the role closest to your work.
Paying for wasteful and abandoned agent sessions?
Give employee agents the priorities, rules, and approved methods that shape good business judgment.
What if every agent session learned from the last?
Turn corrections, reviews, and proven methods into governed context that improves every agent session.
Need agent context control and proof?
Map your agent estate, govern access, and audit the context delivered at a point in time.
Tired of syncing Skills and repository AGENTS.md files?
Manage AGENTS.md and CLAUDE.md guidance, Skills, and Memory once, then keep them current across connected coding agents.
Agent Operations
Equip, align, observe, and improve every agent.
Give agents governed guidance and Skills, align each session with current context, preserve working Memory and Artifacts, pass work between agents, and review conversation records to improve what comes next.
Knowledge
Give agents your shared Knowledge.
Manage shared guidance once, then route the right version into agent work.
Skills
Publish the best way to work.
Turn proven workflows into governed Skills that agents can use across supported tools and teams.
Memory
Keep useful working recall.
Carry decisions, corrections, and active state across sessions without building another knowledge base.
Artifacts
Keep agent work ready to reuse.
Save selected briefs, files, images, and deliverables as versioned packages outside the chat.
Agent monitoring
Review recorded conversations and the context behind them.
Record supported agent conversations alongside the exact context served during work.
Agent messages
Pass work between agents.
Send a note, an exact Artifact version, or both to one connected agent or a Group.
Market context
The numbers behind better agent context.
These studies quantify context efficiency, privacy control, multi-vendor adoption, and productivity with company-specific AI.
- Self-Improving63%fewer tokens with managed contextLodha et al., “Less Context, Better Agents” (2026 preprint). Selective context and summaries raised completion from 71% to 91.6% while reducing token use by 62.6%.Read the source
Self-improving, coordinated agent fleets
Distill and share approved learnings to cut token use and coordinate the fleet across branches, repos, users, models, and harnesses.
- Governed75%less privacy leakage with governed contextWang et al., “Privacy in Action,” Findings of EMNLP (2025). A contextual integrity-based checker reduced privacy leakage from 36.08% to 7.30% and from 33.06% to 8.32% across two models while preserving task helpfulness.Read the source
Agent context governance
Govern what reaches each agent to protect sensitive context, with an audit trail tied to approved versions.
- Portable73%of organizations use multiple AI vendorsIBM Institute for Business Value and Oxford Economics, “The Calculus of AI Sovereignty” (2026). In a survey of 1,000 senior executives, 73% described their AI environments as intentionally multi-vendor.Read the source
Portable, agent-agnostic context & configuration
Manage context, Knowledge, Skills, Memory, MCPs, and plugins once across multiple AI vendors, without lock-in.
- Aligned15%higher worker productivity with company contextBrynjolfsson, Li, and Raymond, “Generative AI at Work,” Quarterly Journal of Economics (2025). The study followed 5,172 customer-support agents using a company-specific AI assistant.Read the source
Agent strategic alignment
Fix cold-start by giving every agent current priorities, context, rules, and Skill access so it can deliver better work, faster and cheaper.
The compounding loop
The fleet learns once, then starts from there.
Good corrections should not disappear inside one chat. Alignbase turns useful working lessons into governed context, reusable Skills, or concise Memory for the next agent session.
- 01Agents start with current context
Direction, approved methods, and working state arrive before the work begins.
- 02Real work produces a useful lesson
A correction, decision, or better method emerges while people and agents work.
- 03The approved lesson improves the fleet
Publish or remember it once, then route it to the sessions that should start ahead.
Start with one team
Make every agent session better than the last.
Connect an agent, publish the context it should use, and let useful work improve what comes next.
Start free