DEW Knowledge Agent
Turn product materials into a cited multilingual knowledge assistant.
Open ↗DEW AI AGENTS
Hire, train, and manage AI agents like a real team
Not another chatbot demo. We define the role, trusted knowledge, permissions, and acceptance first—so answers cite sources, actions stay approvable, and exceptions escalate to people.
Book a fit callWHO THIS FITS
A useful engagement starts with the right problem.
Complex knowledge
Product materials, policies, cases, and SOPs are scattered across people, files, and systems.
Repeated communication
Presales, service, and sales teams answer similar questions without turning those answers into reusable capability.
Governed adoption
You want AI in real operations but cannot accept unsupported answers, unapproved actions, or opaque workflows.
THE CURRENT GAP
What has to change before technology creates value.
A chat, not a role
A general model can converse but has no defined responsibility, permissions, inputs, outputs, or acceptance criteria.
A demo, not an operating model
Real work contains messy data, exceptions, ambiguity, and high-risk decisions that need people.
A launch, not management
Without tests, logs, feedback, cost, and quality review, the agent cannot improve safely.
HOW WE WORK · FDE
Forward Deployed Engineering: from operational reality to production
DEW works directly with customer business and technical teams to define the problem, connect real data and systems, build the smallest useful production loop, and improve it through adoption and operating feedback.
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01 / Discover in context
Enter the real role and workflow to understand users, decisions, knowledge, permissions, and the desired outcome.
Workflow · users · constraints -
02 / Scope the deployment
Define knowledge, evaluations, tool permissions, approvals, logging boundaries, and the smallest pilot.
Scope · risks · acceptance -
03 / Build the smallest useful loop
Build a usable agent loop with real anonymized samples, refusal rules, and human escalation.
Working loop · human fallback -
04 / Deploy into production
Connect the business entry point, test, release, verify permissions, and make escalation explicit.
Release · ownership · exceptions -
05 / Drive adoption and iteration
Improve knowledge and governance from evaluations, approval logs, cost, and business outcomes.
Usage · feedback · improvement
ACCEPTANCE
Define success before expanding scope.
Quality
Evaluate correctness, citations, field completeness, and refusal behavior on an agreed test set.
Efficiency
Measure task time, human review effort, and the volume the agent can handle consistently.
Governance
Verify permissions, approvals, logs, exception handling, and data-use boundaries.
BOUNDARIES
What this engagement does and does not promise.
A pilot is not unattended automation
High-risk actions keep human approval by default. Full automation is not the goal by itself.
No promise of zero errors
Sources, refusal, testing, and review manage model limitations instead of hiding them.
Start narrow
Prove one role is valuable before adding more systems, roles, or autonomy.
FAQ
Questions teams ask before starting.
Do we need a complete knowledge base first?
No. A pilot can start with 10–30 high-use documents and real questions while exposing knowledge gaps.
Can it connect to our CRM, email, or collaboration tools?
Yes, after confirming APIs, account permissions, approvals, and whether the pilot should read or write.
How long does a pilot take?
A well-bounded role with usable materials usually fits a two-to-four-week pilot. Complex integrations are estimated separately.
How do you reduce hallucinations?
We combine trusted retrieval, citations, refusal behavior, test-set evaluation, and human review rather than relying on prompting alone.