Your teams already run AI - what's missing is control. One governed knowledge base, scoped access, and full visibility into what AI does and spends.
Coding agents are your biggest AI spend - and your biggest leak risk. Halofy scopes what every agent sees, pools engineering knowledge in one place, and puts budgets around every run.
Customer truth is scattered across CRM, notes, and support - so every call starts from scratch. Halofy pools it into one knowledge base your team can query from Slack, Teams, and more.
Nobody can say who spent what, on which model, for what outcome. Halofy attributes every token, enforces role-based access, and keeps the knowledge base clean and efficient.
You're funding AI everywhere - but which workflows pay off? Get a granular view of usage and outcomes, and replicate your best people's workflows org-wide.
A generic assistant guesses from the public internet; Halofy's copilot answers from your Business Knowledge Graph - your catalog, orders, refunds, and customer behaviour linked as one live layer - so "which SKUs drove refunds this month, and why?" is one query, not a morning across five dashboards. Faster answers mean you catch the margin leak and the missed sale while they still matter.
You do. Every interaction feeds a knowledge graph that stays yours - the segments, the nudges that convert, the buying signals - first-party intelligence Halofy never trains third parties on, and that you can export at any time. The revenue advantage compounds with you, not a vendor.
You set the guardrails once - tone, discount ceilings, escalation rules - and agents act only within them, so a win-back never breaks your margin floor and a tricky claim routes to a human with the full customer story attached. Every conversation is logged and reviewable.
Yes - Halofy connectors cover the major business backends (Shopify, Salesforce Commerce, BigCommerce, SAP, plus payments and marketing tools), and one connector links any LLM you already use, so it's one integration, not a replatform. First agents typically go live in days, not quarters.
Those are great frameworks for building agents - but you'd still build and maintain the context layer, the integrations, the guardrails, and the cost-optimisation logic yourself, then rebuild it each time the models change. Halofy ships that foundation ready-made and model-agnostic, so your team is live in weeks instead of spending quarters on plumbing.
Three ways: the copilot routes each task to the smallest model that can do it well, the graph supplies context once instead of every tool re-sending it, and the optimisation view flags overlapping AI subscriptions. You see the savings itemised per task, team, and tool - a live number, not a promise.
You own both. Everything the graph learns - your SOPs, your product knowledge, your agents' learnings - stays first-party, is never used to train third-party models, and is fully exportable, so there's no lock-in on the asset you're building.
None in particular, and no. Halofy is model-agnostic by design: connect ChatGPT, Claude, Gemini, or your existing agents through one connector, and swap models later with a config change, not a migration - the knowledge graph outlives any single model choice.
Pricing scales with usage across connected stores, agent conversations, and channels - you pay for what your agents actually do, not for seats. Talk to the team for a plan sized to your volume.
Usage is metered on agent activity rather than a flat per-order tax, and volume tiers bring the unit cost down as you grow. The team will walk you through how your traffic maps to a plan.
Cancel anytime; access continues to the end of the billing period, and everything your workspace has learned remains exportable.
Yes - VAT numbers, purchase orders, and billing contacts can be added from workspace settings.
Update it from workspace settings; changes take effect immediately.
