Step 1
Project creation
Define scope, objectives, timeline, and key stakeholders when starting a new engagement. Link it to a client and team.
Agents that know what you're working on, not just how to work
Project context captures the scope, objectives, timelines, and requirements of each engagement. Agents produce output that is specific to the project at hand — not generic templates waiting to be customized.
Without project context, agents produce technically correct but irrelevant output
Your team might have the best methodology and the deepest client knowledge, but if the AI doesn't know the specific engagement — its scope, constraints, deliverables, and stakeholders — the output misses the mark.
Generic AI forces you to re-explain the project brief every session. Copy-pasting scope documents into prompts is fragile, context windows overflow, and critical details get lost.
The result: agent output that sounds right but addresses the wrong scope, references outdated requirements, or misses project-specific constraints.
What project context captures
Project context is the engagement layer. It anchors agent output to a specific piece of work with defined boundaries, objectives, and deliverables.
This includes engagement scope and objectives, project requirements and constraints, timelines with key milestones and deadlines, deliverable specifications and acceptance criteria, stakeholder details specific to this engagement, and working documents and reference materials uploaded to the project.
Project context is time-bound. When an engagement ends, its context is archived but remains searchable for future reference.
How project context gets built
Step 2
Document upload
Attach SOWs, briefs, requirements documents, and reference materials. AI indexes and structures them for agent retrieval.
Step 3
Progress tracking
As work progresses, project context updates with completed deliverables, decisions made, and evolving requirements.
What lives in project context
Scope & objectives
What the engagement aims to achieve, its boundaries, and the specific outcomes the team is working toward.
Requirements & constraints
Technical requirements, budget constraints, regulatory boundaries, and non-negotiable parameters that shape every deliverable.
Timeline & milestones
Key dates, phase gates, and deadlines that agents reference when discussing urgency, sequencing, and prioritization.
Deliverable specifications
What needs to be produced, in what format, to what standard, and who needs to review it before delivery.
Project stakeholders
Engagement-specific contacts, their roles in this project, and how they differ from the broader client stakeholder map.
Working documents
Uploaded reference materials, meeting notes, and intermediate outputs that agents draw from during the engagement.
How agents use project context
Project context is the most specific layer. When an agent runs within a project scope, it has the full stack: company voice, team methodology, client preferences, and project-specific details. Output is not just on-brand and methodology-aligned — it's anchored to the exact engagement.
A research agent pulls findings relevant to this project's scope. A proposal agent references this engagement's specific objectives. A review agent checks deliverables against this project's acceptance criteria.
The practical effect: less time customizing agent output for each project, fewer errors from stale or wrong context, and agents that genuinely accelerate the work instead of creating editing overhead.
See project context in action
Research & Intelligence
Watch project requirements focus research output on what matters.
See project-aware agents on a real engagement
Book a demo and we will show you how project context eliminates generic output.