Both founders, as a pair
They scope the problem with your lead, design the workflow, build it, and review every change before it ships. You talk directly to the people doing the work.
Forward-deployed engineering
Engineers inside your team until the workflow runs in production.
Forward-deployed engineering means engineers join your team and build inside your systems until a workflow runs in production, instead of advising from outside. At GuildBuild, both founders embed for 4 to 8 weeks with a GuildBuild agent team, then hand the workflow to your people or run it for you.
- Embed length
- 4 to 8 weeks
- The pod
- 2 founders + agent team
- Entry offers
- 2 to 3 weeks or 5 days
- Embeds at a time
- One
The pod
Two founders and an agent team, working inside your systems.
Every embed gets the same pod. We take one embed at a time, so the people you meet on the scoping call are the people who do the work.
A GuildBuild agent team
Agents handle well-bounded engineering tasks under approval gates and cold reviews. Every change they propose is checked before it reaches your systems.
Your people
A named lead and the engineers or analysts who will run the workflow afterwards. They work beside the pod, so the knowledge stays with your team.
How an embed works
Start small. Embed for a few weeks. Keep what works.
Both tracks follow the same three steps.
Start with an entry offer
Start with a Microsoft Fabric or Power BI assessment, or an agent team setup sprint. Each ends with a scoped problem, a security review, and an embed plan.
Embed inside your team
Both founders work inside your tenant or on your machines with a GuildBuild agent team. The embed ends with one workflow in production and the runbooks to run it.
Hand off or operate
Your people take the workflow over, or GuildBuild runs it for you as a managed service. The goal is not dependency.
Two tracks
One pod, two kinds of problem.
Pick the track that matches the problem you want solved first. The pod and the steps are the same.
Microsoft data
For data teams running Microsoft Fabric and Power BI.
Sounds familiar
- Fabric capacity keeps throttling, and nobody can say which workload causes it.
- Executives see different numbers in different reports.
- A Fabric migration is approved, but nobody has picked the first workload.
What an embed ships
One data workflow in production, such as a governed semantic model, a capacity fix with before-and-after evidence, or a first migrated workload running in parallel.
Start with
See the Data LabAgent teams
For engineering organizations adopting coding agents.
Sounds familiar
- Developers use coding agents, but there are no shared rules for what an agent may change.
- Agent output reaches review with no evidence of what was tested.
- Leadership wants a governed rollout, not another pilot that stalls.
What an embed ships
One agent workflow your engineers accept, with approval gates, reviews, and a record of what changed and why.
Start with
Read the field notesGuildBuild in numbers
What the work has delivered.
Outcomes from projects our principals delivered, results measured in our own agent teams, and how long each step takes.
Outcomes from delivered projects
Client-reported figures. Clients are not named yet; a reference for each figure is available on request.
- 16.3%lower average monthly Azure cost year over year, while data and activity grew 30%+Budget use held at 90.3% on an enterprise Fabric platform. Savings of CAD 80,000+ a year came from Azure SQL storage optimization, orchestration and query tuning.
- 2 h → 15 minaverage report refresh time, before and after our Fabric and Power BI workAn approximate average across delivered Fabric and Power BI platforms, from incremental loads, model design and query tuning.
- 7 weeksfrom kickoff to the first governed workload in productionMedian across delivered projects, measured to the first scheduled, monitored workload that users rely on.
- 4,000+engineer-hours of delivery work done by governed agent teams1,020 reviewed pull requests merged in 23 weeks on one client platform, a median of 41 minutes from open to merge. Estimated at 4 hours of human work per change.Estimate
- 167%more analysts with direct access to governed data, across 8+ departmentsAzure SQL mirrored into Fabric and shared to 8+ department workspaces through OneLake shortcuts: no extra copies or extracts, so analysts outside the central team analyze the same data themselves.
- 99.5%of customer records reconciled to source, from 7 systems into oneContact centre, billing, Salesforce, field workforce and legacy ERPs joined into one governed customer record, with quality gates before publish.
What agent orchestration delivers
Measured in GuildBuild’s own agent teams. Each result comes from one published study.
- 28,600calls run by one 20-session agent fleetThe scale we operate at. 98.1% of the fleet’s input was served from cache.
- 87%median context reduction from compactionAcross 196 compactions: far less context for the agent to reread on every later call.
- 55%lower estimated cost for the same perfect scoreThe right model effort scored 40/40 for less than half the estimated cost of the maximum setting, which scored the same.
- 11 minto hand over the work of six agent seatsAfter an account switch, the rebuilt team was checked and ready in 18 minutes.
- 41 of 968shell calls refused by a guard in one sessionRules enforced in code rather than written in prose, so an agent cannot talk its way past them.
- 3high-severity bugs caught before a script’s first runAn independent review of an agent-written migration plan; from first review to last fix took 54 minutes.
Delivery you can plan around
Typical lengths. The scoping call confirms them for your situation.
- 5 daysto an agent workflow running on your repositoryThe Agent Team Setup Sprint ends with one workflow run end to end with your engineers.
- 2 to 3 weeksto a scored Fabric or Power BI planEach assessment ends with a prioritized roadmap or fix plan, a security review, and an embed plan.
- 4 to 8 weeksto one workflow running in productionThe embed ends with the workflow live and the runbooks your team needs to run it.
Project figures are as reported on those projects and do not promise the same result for your business. Agent-team results each come from a single study; open the linked note for its method and limits.
Estimate your agent team
What could an agent team take off your engineers’ plate?
Set your own numbers. The estimate shows the hours returned after review, a starting team size, and how much context the agents would read, using two ratios we measured in our own agent teams.
- Agent seats to start with
- 2
- Context read a day
- 60M
- Context per call after a compaction
- 100k → 13k
- Not served from cache
- 1.1M
Plus one lead seat that assigns work and checks results.
Across all seats, including the lead, before compaction.
Median reduction of 87% across 196 compactions we measured.
At the 98.1% cache share measured in our 20-session fleet.
Hours returned = engineers × hours a week × share taken on × (1 − review time) × 48 weeks. Seats = delegated hours ÷ hours per seat, rounded up.
Check these numbers with us on a scoping callIllustrative planning estimate, not a forecast or a delivered result. The two measured ratios each come from one study of our own agent teams; your workload, models and settings will differ. Returned hours are capacity, not cash savings.
Choosing a model
Forward-deployed engineering, staff augmentation, or a fixed-scope project?
Each model suits a different situation. Forward-deployed engineering fits when the problem is clear but the path runs through your own systems.
| Forward-deployed pod | Staff augmentation | Fixed-scope project | |
|---|---|---|---|
| Best when | The problem is clear, but the path runs through your own systems and people | You know what to build and need more hands | The scope is stable before work starts |
| Who directs the work | GuildBuild and your lead, together | Your team | The vendor, against the agreed scope |
| What you pay for | A short entry offer, then a set number of weeks of a two-person pod with an agent team | Hours or days of each person’s time | An agreed set of deliverables |
| What you end up with | One workflow in production, with runbooks and a team that can run it | Work done under your direction | The deliverables in the statement of work |
| Typical length | 4 to 8 weeks for the embed, plus the entry offer (5 days or 2 to 3 weeks) | Open-ended | Set by the scope |
Ownership
You keep what we build for you.
You own your data, your configuration, and the workflow built for you.
GuildBuild keeps its generic tooling, such as agent team templates and checks, so it can be reused.
The contract names which is which before the embed starts.
At the end, your people take the workflow over, or GuildBuild runs it as a managed service.
Security
Agents work only where you allow them.
Before an embed starts, we agree where your data lives, what the agent team may read or change, and which actions need a person to approve them. The pod works inside your tenant or on machines you control.
Read our security approachQuestions
What buyers ask before an embed.
What is forward-deployed engineering?
Forward-deployed engineering means engineers join your team and build inside your systems until a workflow runs in production, instead of advising from outside. At GuildBuild, both founders embed for 4 to 8 weeks with a GuildBuild agent team, then hand the workflow to your people or run it for you.
How is an embed priced?
We quote each engagement after a scoping call, once we know the problem, the systems involved, and how long the work will take. We do not publish rates. Every engagement starts small, with a Microsoft Fabric or Power BI assessment (2 to 3 weeks) or an agent team setup sprint (5 days).
How long does an embed last?
4 to 8 weeks. The entry offer ends with a scoped problem, a security review, and an embed plan, so the embed starts with an agreed goal.
Who owns the code and configuration?
You own your data, your configuration, and the workflow built for you. GuildBuild keeps its generic tooling, such as agent team templates and checks, so it can be reused. The contract names which is which before the embed starts.
Do you work on site?
GuildBuild is based in Toronto, Ontario, and works with organizations across Canada. Embeds are remote-first, with on-site kickoff and demo days. Delivery arrangements and any data residency requirements are agreed for each engagement.
What happens after the embed?
Your team takes the workflow over with the runbooks we leave behind, or GuildBuild runs it for you as a managed service.
How many embeds does GuildBuild run at once?
One. Both founders work on every embed, so we take one client at a time and agree start dates in advance.
Start with a scoping call
Bring one problem worth solving in the next eight weeks.
Tell us what is slowing your data platform or your engineering team down. We will tell you which entry offer fits, or whether neither does.
contact@guildbuild.ca