A clear breakdown of what Brainforge fixes, how fast, and what it actually delivers.
Copilot builds
Assistants embedded in Slack, CRM, docs, and your product that retrieve approved context and cite their sources.
Copilots your team actually uses, not another pilot
Most copilots die after the demo because they lack context and trust. Brainforge builds copilots that work inside the tools your team already uses — Slack, CRM, docs, and product — with cited answers, human approval on actions, and evals so adoption is real.
In plain terms
What Copilot Implementation means in practice
Where teams get stuck
Copilots inside Slack, CRM, docs, and your product, with cited answers, approval gates, and evals.
Copilot pilots stall because nobody trusts or adopts them.
Assistants give generic answers without your context.
We don't know if the copilot is actually being used or helping.
Sensitive writes happen without review.
What we deliver
Core Copilot Implementation
Approval-gated actions
Copilots draft follow-ups, tickets, CRM notes, and briefs, with human approval on sensitive writes.
Adoption and evals
Usage tracking, quality evals, and iteration so the copilot gets adopted and keeps improving.
How deep it goes
Capabilities behind the work
The same delivery primitives (context, controls, and review) show up across every engagement.
Copilot development
Assistants in Slack, CRM, docs, and product surfaces, built on the stack Brainforge runs internally.
Slack copilotsCRM copilotsProduct copilots
Grounded context
Retrieval over your docs, transcripts, tickets, and CRM so answers carry source trails.
RetrievalCitationsContext engineering
Approved actions
Drafts and writes that stay human-approved and traceable.
Draft follow-upsTicket creationCRM updates
Adoption analytics
Usage tracking and feedback loops that show whether the copilot helps.
Usage metricsFeedback loopsSuccess criteria
Evals and quality
Answer evals and monitoring so quality stays high after launch.
Answer evalsMonitoringIteration
What changes
Outcomes you can point to
- A copilot in the tool your team already works in.
- Answers grounded in your context with citations.
- Approval gates on every sensitive action.
- Usage and quality metrics that prove value.
Proof in production
See where this work shows up.
Campaign copilots reduced reporting cycles 70%
See how AI copilots used unified campaign context to flag underperforming assets and budget misallocations.
Read the copilot case study →Brainforge Assistant is this service running inside our own company
Our internal assistant searches transcripts, HubSpot, Linear, and docs; drafts cited answers; and routes approved workflows in Slack.
See the Slack Assistant proof →Related ways to engage
A clear front door into this work
Common questions
Copilot Implementation, straight answers
What does copilot implementation cost?
Engagements start with a scoped build sprint, so you pay for a bounded piece of work rather than an open-ended retainer. Most teams begin with one copilot in one tool, then expand once adoption and quality are proven.
How long does a copilot implementation take?
A first copilot with retrieval, citations, approval gates, and usage tracking typically ships in 3–6 weeks of sprint work.
Can you build a copilot inside Slack or our CRM?
Yes. Slack-native and CRM-embedded copilots are core to what we build — the Brainforge Assistant that runs inside our own company searches transcripts, HubSpot, Linear, and docs with cited answers and approved actions.
How do you make sure the copilot gets adopted?
We build in the surface where work already happens, track usage against clear success criteria, and iterate from real usage and feedback. Adoption is measured, not assumed.
Can copilots take actions or only answer?
Both, but sensitive writes stay approval-gated and traceable. The copilot drafts follow-ups, tickets, and CRM notes, and a human approves before anything is written.
How we work
A path from pressure to a working system
01
Find the wedge
We pick the copilot use case with the clearest owner and data, where adoption is most likely.
02
Build with context and controls
We wire retrieval, citations, approval gates, and usage tracking into the surface where work happens.
03
Measure and scale
We track adoption and quality, then expand to the next workflow once the first is proven.
Our Trusted Partners
We only bring the best of the best
READY TO PUT
Copilot Implementation to work?
Copilot Implementation to work?
In one working session we'll name what's broken, what's possible, and the first system worth building.
