What we know
Internal processes, product briefs, concepts, variables, success criteria, and deep technical documentation.
An architecture to automate pre-sales and pilots by connecting versioned knowledge, specialized agents, executable skills, and business systems.
A generic agent can draft text. An agent with rules, memory, tools, and procedures can operate consistently.
The system combines a structured knowledge base with executable procedures and secure connections to the tools where the work happens.
Internal processes, product briefs, concepts, variables, success criteria, and deep technical documentation.
Skills that turn recurring procedures into executable instructions, with steps, tools, and checks.
Status, scope, decisions, meetings, follow-ups, and outcomes for each process, versioned over time.
Automation is not a single action: it is a chain that interprets, verifies, asks for approval, writes to the right systems, and keeps context.
The agent interprets the commercial requirement, separates facts from assumptions, and detects missing information.
It checks that a use case, a product, and a real technical need exist. It looks for duplicates before creating anything.
It proposes process type, pipeline, description, owners, and fields; a person confirms before anything is written.
It creates the ticket and, in the same flow, opens or updates the versioned context with a uniform structure.
It turns the meeting into a note, status, follow-ups, and CRM progress without recapturing everything by hand.
It queries follow-ups and stages, assigns the right ownership, and keeps decisions and outcomes traceable.
The commercial role keeps global progress. The technical role owns agreements, answers, and engineering tasks.
The technical role owns organization and follow-up: real scope, success criteria, checklist, dates, risks, and results.
The agent crosses calendar, attendees, and note sources; it checks that real content exists and propagates agreements once.
A skill packages the when, the how, the allowed tools, known failure modes, and how to verify the result.
Triggered by intentThe agent recognizes when to apply the procedure.
Shrinks the decision spaceIt orders steps, sources, and exceptions before acting.
Limits the toolsIt declares least privilege and approval gates.
Accumulates experienceReal errors become gotchas and recipes.
They orchestrate work across people, systems, and the repository.
They turn technical documentation into safe API operations.
They prepare technical changes with review and controlled deployment.
Product skills combine documentation, scripts, and diagnostics to turn a complex API into a repeatable, safe sequence.
GETTESTPOSTGETGITConnectors standardize access to business systems. Direct APIs cover deep product operations. The repository keeps the context that joins both worlds.
Tickets, pipelines, notes, owners, duplicate search, and follow-up.
MCP · controlled read and writeMeeting discovery, attendees, acceptance, and time context.
MCP · structured querySummaries, transcripts, and agreements turned into actionable context.
MCP · content retrievalOn-demand lookup of official references and behavior validation.
Web / API lab · researchConfiguration, diagnosis, tests, and repeatable operations with scripts.
Direct API · specialized executionProgress, alerts, and questions about missing information in the working channel.
Connector · proactive communicationContext → decision → action → evidence
Useful autonomy does not mean unlimited access. The system defines what it can read, what it can prepare, and what needs human confirmation.
Tickets, external notes, proposals, and high-impact changes go through a preview and approval.
Tokens and credentials live in environment variables; never in documents, conversations, or commits.
The agent confirms scope, validates sources, and asks under ambiguity instead of filling gaps with assumptions.
It keeps commercial and technical context, not sensitive data about end users or private evidence.
Changes are dated, versioned, and tied to a source, a decision, or an owner.
Each skill declares which tools it may use and verifies state before and after a mutation.
It is not only about generating text faster. It reduces search, context switching, repeated typing, lost agreements, and dependence on individual knowledge.
Status, decisions, and documentation stop living across chats, notes, and individual memory.
The same conversation feeds the repository, the CRM, and the follow-up channel.
Skills reuse API procedures, diagnostics, and guardrails already learned.
Every missing piece of information becomes a follow-up, and every ticket has associated context.
A new person or agent can understand the process by reading the same versioned source.
Automation prepares and executes; sensitive decisions keep a human gate.
Corrections are not lost in a conversation. They become rules, calibrations, references, edge cases, and new verification steps.
Autonomy is built once memory, procedures, and permissions are already trustworthy.
Rules, processes, templates, and knowledge live in Git.
Skills guide frequent tasks and reduce variability.
MCP and APIs link CRM, calendar, notes, and product.
Loops review follow-ups, ask questions, and report with guardrails.
Repository as memory. Agents as operators. Skills as procedures. MCP and APIs as connections. People as owners of the decisions.