Capabilities we engineer
- Goal-driven planning with large language models (Amazon Bedrock)
- Tool calling: APIs, databases, search, CRM and ERP operations
- Retrieval-Augmented Generation over your documents and catalogs
- Memory: conversation state plus persistent business context
- Guardrails: policy filters, restricted permissions, sensitive-data handling
- Human-in-the-loop workflows with escalation and takeover
- Multi-agent orchestration with a supervisor pattern
- Observability: full traces, evaluation suites and cost monitoring
Reference architecture
Channel (WhatsApp / Web / Marketplace / API)
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Develo AI Layer (routing, context, guardrails)
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LLM Agent (Amazon Bedrock) — plans and calls tools
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Tools / MCP servers
├── CRM ├── Orders / Ecommerce
├── Catalog ├── Internal APIs
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Human operators (escalation, takeover, supervision)Business use cases we ship
Customer support agents
Answer product, order and policy questions using live business data.
Learn more →WhatsApp agents
24/7 conversational support with natural language and human escalation.
Learn more →Marketplace agents
Automate buyer questions and seller operations on marketplaces.
Learn more →Operational agents
Internal copilots that run multi-step workflows across your systems.
Frequently asked questions
What can an AI agent do that a chatbot cannot?
A chatbot matches intents to canned responses. An agent pursues a goal: it plans steps, calls APIs, reads your databases, adapts to new information and completes multi-step tasks such as checking an order, applying a policy and escalating to a human when needed.
How do AI agents access our internal data safely?
Agents get scoped, read-mostly access through tool definitions — often exposed via the Model Context Protocol (MCP). Permissions, audit logs and guardrails restrict what each agent can do, and sensitive actions require human approval.
What happens when an agent is not sure?
We design explicit human-in-the-loop checkpoints: confidence thresholds, policy rules and escalation paths route uncertain or high-stakes conversations to your operators, with full context attached.
How do you measure agent quality?
Every agent ships with an evaluation suite: replayed business conversations checked for correctness, policy compliance and tone, run on every change to prompts, tools or models, plus production observability (traces, cost, escalation rate).
Related
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Pick one high-volume workflow and we'll prototype an agent that handles it end to end.
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