You are implementing for the first time
You have bought licences and need a working org in a quarter, not a year. We run discovery, design the data model and ship in fixed phases.
See the implementation phases
Salesforce
Salesforce implementation by an AI-first engineering firm
We design, build and run Sales, Service, Marketing and Experience Cloud, then connect your CRM to LLMs, knowledge bases and agents so the data inside it starts doing work.
- Apex, LWC, Flow, Agentforce
- Fixed-scope phases
- Senior people, small teams
Who this is for
Three situations we are usually called into
Salesforce is rarely the problem. The problem is an org that grew without a design, integrations nobody owns, or an AI ambition with no path into the CRM.
Your org has years of technical debt
Workflow rules, Process Builder, triggers nobody dares touch, profiles with everything ticked. We score it and decide: fix in place or re-implement.
Run an org health checkYou want AI in the CRM, properly
Lead scoring, case summaries, drafted emails, answers from your knowledge base. We decide where Agentforce fits and where an external model does the job better.
Build a Salesforce AI roadmap
What we do
Twelve Salesforce services, grouped by what you need now
Implement a cloud, extend what you have with code, AI and integrations, or hand us the running of it.
Implement
Salesforce Implementation
Greenfield builds and re-implementations in seven phases with fixed deliverables and typical durations.
ExploreSales Cloud
Pipeline stages that match how you sell, forecasting people trust, lead routing and CPQ-readiness.
ExploreService Cloud
Case management, omnichannel routing, knowledge, entitlements and AI deflection that knows when to hand off.
ExploreMarketing Cloud
Journeys, segmentation, consent and data extensions, and a plain explanation of Engagement versus Account Engagement.
ExploreExperience Cloud
Partner and customer portals with a sharing model that stays secure as the user base grows.
ExploreExtend
Agentforce & Einstein
What the native agents can do, where they fit, and when an external LLM is the better tool.
ExploreApex & LWC Development
Code only where Flow cannot, with a trigger framework, tests and a release pipeline that survives audits.
ExploreIntegrations
REST, Platform Events, Change Data Capture, Bulk API or MuleSoft, chosen by latency, volume and ownership.
ExploreData Migration
Profile, map, dedupe, load and reconcile, with a cutover plan and a rollback you have actually rehearsed.
ExploreRun
Managed Services
Admin, release management and monitoring in three tiers, with a backlog you own and no lock-in.
ExploreOrg Health Check
A scored audit of technical debt, security, performance and adoption, with a prioritised fix list.
ExploreSalesforce AI Roadmap
Where AI pays off in your CRM, ranked by value and effort, laid out over twelve months with metrics.
Explore
Why us
Salesforce specialists who also build the AI around it
Most Salesforce consultancies stop at the edge of the org. We are an AI consulting and engineering firm with a Salesforce practice inside it, which changes what we can build for you.
- Agents that read your contracts, tickets and product docs through a knowledge base (RAG), not only CRM fields
- MCP servers that expose Salesforce objects and Flows as tools for Claude, GPT or Gemini, with permission checks
- Evaluation and monitoring for every AI feature, so a summariser that drifts gets caught before your reps do
- Security reviewed as AI security: prompt injection through case text, data leaving the org, audit trails
- The same engineers also write Apex, LWC, Python and Node, so nothing falls between two vendors
Read Salesforce and LLMs: what actually works for the patterns we recommend and the ones we avoid.
“The question is never ‘can Salesforce do this?’ It is ‘should this live in the org, next to it, or in a model we can swap?’ We answer that before anyone configures anything.”
Teksmobile Salesforce practice lead
ApexLWCFlowAgentforcePlatform EventsMuleSoftClaudeMCPpgvector
Process
How an implementation runs
Seven phases, each with a named deliverable and a sign-off. A single-cloud implementation typically takes 8–16 weeks; multi-cloud programmes 4–6 months.
Discovery
Interviews, process maps, data profiling. Output: scope, risks, phase plan. 1–3 weeks.
Design
Data model, security model, automation and integration design, approved on paper first. 2–4 weeks.
Build
Configuration, Flow, Apex and LWC in sprints with demos every one to two weeks. 4–8 weeks.
Data
Migration rehearsals, dedupe and reconciliation reports, run alongside build. 2–6 weeks.
UAT
Scripted scenarios run by your users, defects triaged daily, exit criteria agreed up front. 1–3 weeks.
Go-live
Freeze, final delta load, cutover checklist, training and a rollback plan nobody expects to use.
Hypercare
Daily stand-ups with your admins, fast fixes, adoption metrics, then a clean handover. 2–4 weeks.
Each phase, its deliverables and the decision between fixing and re-implementing are detailed on the implementation page. Our broader delivery principles are on How we work.
Related
Where Salesforce meets the rest of what we do
Solution
Sales copilot
Call prep, meeting notes and next steps written back to opportunities.
Read SolutionCustomer support AI
Deflect, assist and escalate with answers grounded in your knowledge articles.
Read IndustryFintech
Onboarding, KYC case handling and compliance-aware automation in regulated CRMs.
Read GlossaryWhat is Agentforce?
A plain-English definition of Salesforce's agent platform and its building blocks.
Read
FAQ
Frequently asked questions
Are you a Salesforce partner?
We are Salesforce implementation specialists working inside an AI consulting and engineering firm founded in 2006. Ask us about our current partner status and the certifications on the team during a scoping call; we would rather show you the people than a badge.
How long does a Salesforce implementation take?
A single-cloud implementation typically runs 8–16 weeks from discovery to go-live, followed by 2–4 weeks of hypercare. Multi-cloud programmes with integrations and data migration usually take 4–6 months. See how we phase an implementation.
Should we use Agentforce or an external LLM such as Claude?
Use Agentforce when the agent lives entirely inside Salesforce and works on CRM data. Use an external model through our MCP and RAG services when the agent needs documents, systems or reasoning that sit outside the org, or when you want model choice and cost control. We explain the trade-offs on the Agentforce and Einstein page.
Our org is a mess. Do we need to start again?
Usually not. A health check scores technical debt, security, performance and adoption in 2–3 weeks and tells you whether to fix in place or re-implement. Most orgs are fixable; the decision table on the implementation page shows where the line sits.
Can you support an org you did not build?
Yes. Managed services start with a short discovery of the existing org, documentation of what we find, and a backlog you approve. We take over admin, releases and monitoring in tiers without a long-term lock-in.